paper_name stringlengths 4 421 | paper_url stringlengths 21 200 | paper_authors listlengths 0 125 | paper_abstract stringlengths 0 43.4k | paper_code stringlengths 1 139 | conf stringlengths 6 18 |
|---|---|---|---|---|---|
More Than Pivot for Maximal Clique Enumeration | https://doi.org/10.1109/ICDE65706.2026.00097 | [
"Zhaoyi Zhong",
"Rui Zhou",
"Lu Chen",
"Xiaofan Li",
"Chengfei Liu"
] | The Maximal Clique Enumeration (MCE) problem is a classic and fundamental task in graph data mining and analysis. It has attracted widespread attention due to its broad applications in areas such as social network analysis and bioinformatics. A widely adopted framework for solving the MCE problem is the Bron-Kerbosch (... | # | ICDE2026 |
Provsql: a General System for Keeping Track of the Provenance and Probability of Data | https://doi.org/10.1109/ICDE65706.2026.00098 | [
"Aryak Sen",
"Silviu Maniu",
"Pierre Senellart"
] | We present the data model, design choices, and performance of ProvSQL, a general and easy-to-deploy provenance tracking and probabilistic database system implemented as a PostgreSQL extension. ProvSQL's data and query models closely reflect that of a large core of SQL, including multiset semantics, the full relational ... | # | ICDE2026 |
Data Guard: A Fine-Grained Purpose-Based Access Control System for Large Data Warehouses | https://doi.org/10.1109/ICDE65706.2026.00099 | [
"Khai Tran",
"Sudarshan Vasudevan",
"Pratham Desai",
"Alex Gorelik",
"Mayank Ahuja",
"Athrey Yadatore Venkateshababu",
"Mohit Verma",
"Dichao Hu",
"Walaa Eldin Moustafa",
"Vasanth Rajamani",
"Ankit Gupta",
"Issac Buenrostro",
"Kalinda Raina",
"Yanwen Lin"
] | The last few years have witnessed a spate of data protection regulations in conjunction with an ever-growing appetite for data usage in large businesses, which presents significant challenges for businesses to maintain compliance. To address this conflict, we present Data Guard - a finegrained, purpose-based access con... | # | ICDE2026 |
Fine-Grained Manipulation Attacks to Local Differential Privacy Protocols for Range Query | https://doi.org/10.1109/ICDE65706.2026.00100 | [
"Xinyu Li",
"Wenda Chen",
"Xuebin Ren"
] | Local Differential Privacy (LDP) enables massive sensitive data collection and analysis without any trusted aggregator, thus having been widely deployed by large corporations. However, recent studies indicate that LDP protocols can be easily disrupted by poisoning or manipulation attacks. In particular, manipulation at... | # | ICDE2026 |
GPU-Accelerated OLTP: An in-Depth Analysis of Concurrency Control Schemes | https://doi.org/10.1109/ICDE65706.2026.00102 | [
"Zihan Sun",
"Yuyu Luo",
"Yong Zhang",
"Chao Li",
"Chunxiao Xing"
] | Over the past decade, GPUs have demonstrated significant potential in accelerating Online Analytical Processing (OLAP) operations. However, there remains a substantial gap in their application to Online Transaction Processing (OLTP), as GPUs were traditionally considered unsuitable for such workloads. Despite this perc... | # | ICDE2026 |
Semantic Publish/Subscribe Over Evolving Topics | https://doi.org/10.1109/ICDE65706.2026.00103 | [
"Yiming Yao",
"Lisi Chen",
"Shuo Shang"
] | The continued explosion of data from social media, news feeds, and online forums has intensified the demand for efficient and precise content dissemination. Traditional similaritybased publish/subscribe systems rely on text similarity metrics, failing to capture semantic distinctions between similar phrases. So far, tr... | https://github.com/yyyyyyyan7/DISPS | ICDE2026 |
FusAD: Time-Frequency Fusion with Adaptive Denoising for General Time Series Analysis | https://doi.org/10.1109/ICDE65706.2026.00104 | [
"Da Zhang",
"Bingyu Li",
"Zhiyuan Zhao",
"Feiping Nie",
"Junyu Gao",
"Xuelong Li"
] | Time series analysis plays a vital role in fields such as finance, healthcare, industry, and meteorology, underpinning key tasks including classification, forecasting, and anomaly detection. Although deep learning models have achieved remarkable progress in these areas in recent years, constructing an efficient, multi-... | https://github.com/zhangda1018/FusAD | ICDE2026 |
Damba-ST: Domain-Adaptive Mamba for Efficient Urban Spatio-Temporal Prediction | https://doi.org/10.1109/ICDE65706.2026.00105 | [
"Rui An",
"Yifeng Zhang",
"Ziran Liang",
"Wenqi Fan",
"Yuxuan Liang",
"Xuequn Shang",
"Qing Li"
] | Training urban spatio-temporal foundation models that generalize well across diverse regions and cities is critical for deploying urban services in unseen or data-scarce regions. Recent studies have typically focused on fusing cross-domain spatio-temporal data to train unified Transformer-based models. However, these m... | # | ICDE2026 |
Beyond Traditional Diagnostics: Transforming Patient-Side Information Into Predictive Insights with Knowledge Graphs and Prototypes | https://doi.org/10.1109/ICDE65706.2026.00106 | [
"Yibowen Zhao",
"Yinan Zhang",
"Zhixiang Su",
"Li-Zhen Cui",
"Chunyan Miao"
] | Predicting diseases solely from patient-side information, such as demographics and self-reported symptoms, has attracted significant research attention due to its potential to enhance patient awareness, facilitate early healthcare engagement, and improve healthcare system efficiency. However, existing approaches encoun... | # | ICDE2026 |
SSFusion: Tensor Fusion with Selective Sparsification for Efficient Distributed DNN Training | https://doi.org/10.1109/ICDE65706.2026.00107 | [
"Zhangqiang Ming",
"Rui Wang",
"Yuchong Hu",
"Yuanhao Shu",
"Wenxiang Zhou",
"Xinjue Zheng",
"Dan Feng"
] | Distributed deep neural networks (DNN) training systems deployed across multiple workers have been widely used to accelerate the training of large models and datasets, while the communication overhead for synchronizing data (i.e., gradient tensor) among workers often becomes a performance bottleneck. To improve communi... | # | ICDE2026 |
MojoFrame: Dataframe Library in Mojo Language | https://doi.org/10.1109/ICDE65706.2026.00108 | [
"Shengya Huang",
"Zhaoheng Li",
"Derek Werner",
"Yongjoo Park"
] | Mojo is an emerging programming language built on MLIR (Multi-Level Intermediate Representation) and supports JIT (Just-in-Time) compilation. It enables transparent hardwarespecific optimizations (e.g., for CPUs and GPUs), while allowing users to express their logic using Python-like user-friendly syntax. Mojo has demo... | # | ICDE2026 |
Text2VectorSQL: Towards a Unified Interface for Vector Search and SQL Queries | https://doi.org/10.1109/ICDE65706.2026.00109 | [
"Zhengren Wang",
"Dongwen Yao",
"Bozhou Li",
"Dongsheng Ma",
"Bo Li",
"Zhiyu Li",
"Feiyu Xiong",
"Bin Cui",
"Linpeng Tang",
"Wentao Zhang"
] | The proliferation of unstructured data poses a fundamental challenge to traditional database interfaces. While Text-to-SQL has democratized access to structured data, it remains incapable of interpreting semantic or multi-modal queries. Concurrently, vector search has emerged as the de facto standard for querying unstr... | https://github.com/OpenDCAI/Text2VectorSQL | ICDE2026 |
Rethinking Flexible Graph Similarity Computation: One-Step Alignment with Global Guidance | https://doi.org/10.1109/ICDE65706.2026.00111 | [
"Zhouyang Liu",
"Ning Liu",
"Yixin Chen",
"Jiezhong He",
"Shuai Ma",
"Dongsheng Li"
] | Graph Edit Distance (GED) is a widely used measure of graph similarity, valued for its flexibility in encoding domain knowledge through operation costs. However, existing learning-based approximation methods follow a modeling paradigm that decouples local candidate match selection from both operation costs and global d... | https://github.com/liuzhouyang/GEN | ICDE2026 |
Beyond Homophily: Community Search on Heterophilic Graphs | https://doi.org/10.1109/ICDE65706.2026.00112 | [
"Qing Sima",
"Xiaoyang Wang",
"Wenjie Zhang"
] | Community search aims to identify a refined set of nodes that are most relevant to a given query, supporting tasks ranging from fraud detection to recommendation. Unlike homophilic graphs, many real-world networks are heterophilic, where edges predominantly connect dissimilar nodes. Therefore, structural signals that o... | # | ICDE2026 |
Efficient Cloud-Edge Collaborative Approaches to Sparql Queries Over Large RDF Graphs | https://doi.org/10.1109/ICDE65706.2026.00113 | [
"Shidan Ma",
"Peng Peng",
"Xu Zhou",
"M. Tamer Özsu",
"Lei Zou",
"Guo Chen"
] | With the increasing use of RDF graphs, storing and querying such data using SPARQL is a critical problem. Current solutions rely on cloud-based data management architectures, but often suffer from performance bottlenecks when bandwidth is limited or system load is high. We explore, for the first time, an edge computing... | https://github.com/msd673/edgeComputing_gurobi.git | ICDE2026 |
Generalizable Address-Aware Semantic Prefetching for Scalable Transactional and Analytical Workloads | https://doi.org/10.1109/ICDE65706.2026.00114 | [
"Farzaneh Zirak",
"Farhana Choudhury",
"Renata Borovica-Gajic"
] | Data prefetching plays a crucial role in reducing I/O overhead and improving the performance of database systems. While traditional prefetchers focus on sequential patterns, recent learning-based approaches, especially those leveraging data semantics, achieve higher accuracy for complex access patterns. However, these ... | # | ICDE2026 |
AlignSketch: A Framework for Aligning Theoretical and Practical Estimation Errors | https://doi.org/10.1109/ICDE65706.2026.00115 | [
"Ce Zheng",
"Hanyue Zheng",
"Jingwei Shi",
"Xinye Xu",
"Wei Zhou",
"Tong Yang",
"Zhenyu Guan",
"Yong Cui"
] | Sketches are widely used in data streams and approximate query processing for their low memory and acceptable errors. They can be categorized into non-classificationbased and classification-based sketches. While the latter typically provide higher accuracy, they often involve fragmented stream processing, which increas... | # | ICDE2026 |
FedCurrMM: A Federated Map Matching Framework with Curriculum-Aware Client Selection | https://doi.org/10.1109/ICDE65706.2026.00116 | [
"Minxiao Chen",
"Haitao Yuan",
"Haoning Wang",
"Nan Jiang",
"Zhihan Zheng",
"Ao Zhou",
"Shangguang Wang"
] | Federated map matching aims to align GPS trajectories collected by multiple decentralized clients to road networks in a privacy-preserving manner, and remains an unexplored yet critical problem for collaboration across clients. However, this task is highly challenging due to severe client heterogeneity, which hinder ef... | # | ICDE2026 |
Enabling Homomorphic Analytical Operations on Compressed Scientific Data with Multi-Stage Decompression | https://doi.org/10.1109/ICDE65706.2026.00117 | [
"Xuan Wu",
"Sheng Di",
"Tripti Agarwal",
"Kai Zhao",
"Xin Liang",
"Franck Cappello"
] | Error-controlled lossy compressors have been widely used in scientific applications to reduce the unprecedented size of scientific data while keeping data distortion within a userspecified threshold. While they significantly mitigate the pressure for data storage and transmission, they prolong the time to access the da... | # | ICDE2026 |
DNA: A Distribution-and-Aggregation Solution for Spatiotemporal K-Function-Based Analysis | https://doi.org/10.1109/ICDE65706.2026.00118 | [
"Tsz Nam Chan",
"Bojian Zhu",
"Dingming Wu",
"Renchi Yang",
"Ruisheng Wang"
] | Generating a spatiotemporal $K$-function plot is frequently adopted to analyze point patterns by domain experts in a wide range of application domains, including criminology, transportation science, urban planning, and epidemiology. However, with the high worst-case time complexity of computing a spatiotemporal $K$-fun... | https://github.com/edisonchan2013928/DNA | ICDE2026 |
Chubby: Robust Smart Contract Execution Against Dependency Over-Declaration | https://doi.org/10.1109/ICDE65706.2026.00119 | [
"Junyu Wei",
"Xiaodong Qi",
"Qifeng Que",
"Zhao Zhang",
"Yanqin Yang",
"Cheqing Jin"
] | The adoption of pre-declared read/write sets (RWSets) in blockchains such as Solana enables parallel transaction execution by identifying non-conflicting transactions in advance. However, this approach is highly sensitive to RWSet accuracy: conservative over-approximation or adversarial manipulation can introduce false... | # | ICDE2026 |
PLAN: Fast and Approximate Gaussian Kernel Density Visualization in Road Networks | https://doi.org/10.1109/ICDE65706.2026.00120 | [
"Tsz Nam Chan",
"Hongwei Ye",
"Bojian Zhu",
"Leong Hou U",
"Dingming Wu",
"Ruisheng Wang",
"Joshua Zhexue Huang"
] | Network Kernel Density Visualization (NKDV) is a widely used spatial analysis tool in various communities, including transportation science, criminology, and urban planning. However, generating NKDV is very time-consuming, which does not scale to support large-scale datasets. Although many efficient algorithms have bee... | https://github.com/edisonchan2013928/PLAN | ICDE2026 |
MINOR: Multivariate Time Series Iterative Cleaning Algorithm | https://doi.org/10.1109/ICDE65706.2026.00121 | [
"Aoqian Zhang",
"Yinru Sun",
"Pengxiang Hao",
"Yifeng Gong",
"Boyang Li",
"Jing Geng",
"Zheng Wang",
"Lianpeng Qiao"
] | Errors are common in time series data, such as sensor measurements. Existing methods tend to focus on single errors in univariate data, but do not provide satisfactory results for consecutive errors, especially in the more general multivariate data. Modeling each dimension separately in one run can lead to bias, as the... | # | ICDE2026 |
From Single to Multiple Attributes: Experimental Insights on Sampling-Based Distinct Combination Estimation in Group-by Queries | https://doi.org/10.1109/ICDE65706.2026.00122 | [
"Yujie Zhang",
"Xiaochun Yang",
"Bin Wang",
"Yuan Sui"
] | Estimating the number of distinct combinations in multi-attribute GROUP-BY queries remains a significant yet underexplored challenge. Current cardinality estimation techniques primarily focus on SPJ queries (i.e., selections, projections, and joins) and neglect GROUP-BY operations; meanwhile, distinct value estimation ... | # | ICDE2026 |
Explaining GNN Negatives Globally and Locally | https://doi.org/10.1109/ICDE65706.2026.00123 | [
"Kehan Pang",
"Wenfei Fan",
"Min Xie",
"Dandan Lin"
] | This paper studies explanations for graph neural network (GNN) classifiers $\mathcal{M}$ when $\mathcal{M}$ makes negative predictions, such as loan denials, paper rejections, or job application turn-downs. The objective is to (a) provide global explanations of $\mathcal{M}$'s behavior and (b) generate counterfactual e... | # | ICDE2026 |
Scaling Subsequence Similarity Join Based on Dynamic Time Warping | https://doi.org/10.1109/ICDE65706.2026.00124 | [
"Zemin Chao",
"Qiaoyi Zheng",
"Xingxing Xiao",
"Boyu Xiao",
"Zhixin Qi",
"Hongzhi Wang"
] | Subsequence similarity join is an important operation in time series analysis, widely employed for the identification of conserved or recurring patterns. Although Dynamic Time Warping (DTW) is widely recognized as an effective similarity measure due to its robustness to temporal distortions, its high computational cost... | # | ICDE2026 |
Overcoming the Sync-Compute Dilemma in Parallel Graph-Based Vector Retrieval | https://doi.org/10.1109/ICDE65706.2026.00125 | [
"Qiji Mo",
"Zhiyuan Hua",
"Zebin Yao",
"Lixiao Cui",
"Gang Wang",
"Xiaoguang Liu",
"Zijing Wei",
"Xinyu Liu",
"Tianxiao Tang",
"Shaozhi Liu",
"Lin Qu"
] | Approximate Nearest Neighbor Search (ANNS) is fundamental to modern applications such as Retrieval-augmented Generation. Among various ANNS algorithms, graph-based methods have become the state-of-the-art due to their excellent search efficiency. The core of graph-based methods is to perform a Best-First Search (BFiS) ... | # | ICDE2026 |
Procore: Robust Core-Set Selection Via Pareto Multi-Dimensional Optimization From Noisy Data | https://doi.org/10.1109/ICDE65706.2026.00126 | [
"Xiaoou Ding",
"Hongbin Hu",
"Songnan Jiang",
"Muyun Zhou",
"Chen Wang",
"Jingru Yang",
"Hongzhi Wang"
] | In large-scale, data-driven machine learning tasks, efficiently selecting representative subsets from noisy datasets is a key challenge for training efficiency and model robustness. Existing coreset selection methods typically rely on singleobjective criteria and lack principles to handle noise, leading to biased or un... | # | ICDE2026 |
NebulaStream: An Adaptive and Efficient Multi-Query Stream Processing Engine | https://doi.org/10.1109/ICDE65706.2026.00127 | [
"Nils L. Schubert",
"Lukas Schwerdtfeger",
"Sara Schnaterbeck",
"Philipp M. Grulich",
"Bonaventura Del Monte",
"Steffen Zeuch",
"Volker Markl"
] | Existing Stream Processing Engines (SPEs), designed for scale-out in the cloud, often overlook the need for scaleup performance on heterogeneous hardware. As a result, they provide latency and throughput guarantees at the expense of high overhead on system resources, for example, memory and CPU usage. This over-provisi... | # | ICDE2026 |
An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs | https://doi.org/10.1109/ICDE65706.2026.00128 | [
"Waleed Afandi",
"Hussein Abdallah",
"Ashraf Aboulnaga",
"Essam Mansour"
] | Efficient inference for graph neural networks (GNNs) on large knowledge graphs (KGs) is essential for many real-world applications. GNN inference queries are computationally expensive and vary in complexity, as each involves a different number of target nodes linked to subgraphs of diverse densities and structures. Exi... | # | ICDE2026 |
Tetris: Lightweight Hyperparameter Auto-Tuning for Mitigating Performance Spikes in LSM-KVS | https://doi.org/10.1109/ICDE65706.2026.00129 | [
"Yina Lv",
"Wenhao Zhu",
"Qiao Li",
"Quanqing Xu",
"Congming Gao",
"Chuanhui Yang",
"Xiaoli Wang",
"Chun Jason Xue"
] | LSM-trees have been widely adopted in modern database systems owing to their log-structured design and sequential write efficiency. This design makes them particularly suitable for write-intensive, large-scale scenarios. However, a critical challenge lies in the flush and compaction processes in the LSM-tree, which oft... | # | ICDE2026 |
An End-To-End Re-Evaluation of Table Entity-Linkers | https://doi.org/10.1109/ICDE65706.2026.00130 | [
"Martin Pekár Christensen",
"Matteo Lissandrini",
"Katja Hose"
] | Abstract Knowledge graph (KG) entity linkers link entity mentions from a source data representation to their corre sponding entities in a target KG. A knowledge graph (KG) is a popular graph model expressing semantic information about entities, concepts, and relationships. Consequently, entity linking from tables to KG... | # | ICDE2026 |
Cole ${ }^{+}$: Towards Practical Column-Based Learned Storage for Blockchain Systems | https://doi.org/10.1109/ICDE65706.2026.00132 | [
"Ce Zhang",
"Cheng Xu",
"Haibo Hu",
"Jianliang Xu"
] | Blockchain provides a decentralized and tamperresistant ledger for securely recording transactions across a network of untrusted nodes. While its transparency and integrity are beneficial, the substantial storage requirements for maintaining a complete transaction history present significant challenges. For example, Et... | # | ICDE2026 |
Efficient Meta-Path Constrained Reachability Query on Heterogeneous Information Networks | https://doi.org/10.1109/ICDE65706.2026.00133 | [
"Chao Ni",
"Zi Chen",
"Long Yuan",
"Bolong Zheng",
"Lu Qin"
] | Heterogeneous information networks (HINs) are prevalent in real-world applications, capturing complex semantic relationships through multiple types of entities and links. Metapath constrained reachability (MCR) queries, which ask whether two vertices are connected via a simple path under given metapath pattern, are fun... | # | ICDE2026 |
HEXGEN-FLOW: Optimizing LLM Inference Request Scheduling for Agentic Text-to-SQL | https://doi.org/10.1109/ICDE65706.2026.00134 | [
"You Peng",
"Youhe Jiang",
"Wenqi Jiang",
"Chen Wang",
"Binhang Yuan"
] | Recent advances in agentic large language models (LLMs) have substantially improved Text-to-SQL, enabling users without database expertise to query databases intuitively. However, deploying agentic LLM-based Text-to-SQL systems in production remains challenging due to multi-stage dependencies, strict latency requiremen... | # | ICDE2026 |
Krone: Hierarchical and Modular Log Anomaly Detection | https://doi.org/10.1109/ICDE65706.2026.00135 | [
"Lei Ma",
"Jinyang Liu",
"Tieying Zhang",
"Peter M. VanNostrand",
"Dennis M. Hofmann",
"Lei Cao",
"Elke A. Rundensteiner",
"Jianjun Chen"
] | Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions with clear boundaries, this structure is lost when stored as flat sequences. Hence, state-of-theart methods risk missing true dependencies within executions while learning spuriou... | https://github.com/LeiMa0324/Krone_official/ | ICDE2026 |
MINT: Multi-Vector Search Index Tuning | https://doi.org/10.1109/ICDE65706.2026.00136 | [
"Jiongli Zhu",
"Yue Wang",
"Bailu Ding",
"Philip A. Bernstein",
"Vivek R. Narasayya",
"Surajit Chaudhuri"
] | Vector search plays a crucial role in many real-world applications. In addition to single-vector search, multi-vector search becomes important for multi-modal and multi-feature scenarios today. In a multi-vector database, each row is an item, each column represents a feature of items, and each cell is a high-dimensiona... | # | ICDE2026 |
LLM4Hint: Leveraging Large Language Models for Hint Recommendation in Offline Query Optimization | https://doi.org/10.1109/ICDE65706.2026.00137 | [
"Suchen Liu",
"Yang Lin",
"Yinjun Han",
"Jun Gao"
] | Query optimization is essential for efficient SQL query execution in DBMS, and remains attractive over time due to the growth of data volumes and advances in hardware. Existing traditional optimizers struggle with the cumbersome hand-tuning required for complex workloads, and the learning-based methods face limitations... | # | ICDE2026 |
CFDGraph: Privacy-Preserving Graph Processing for Large-Scale Collaborative Fraud Detection | https://doi.org/10.1109/ICDE65706.2026.00138 | [
"Qiulin Wu",
"Amelie Chi Zhou",
"Tristan Allard",
"Shadi Ibrahim",
"Yuhong Feng",
"Lichun Li",
"Amr El Abbadi"
] | Fraud detection is a critical task in finance and e-commerce, but fraudsters increasingly evade detection by distributing their activities across multiple institutions. While this makes collaborative fraud detection (CFD) essential, it is hindered by two fundamental barriers: stringent data privacy regulations and cons... | # | ICDE2026 |
SNI-GNN: SmartNIC-Assisted Full-Graph GNN Training with In-Network Embedding Prediction | https://doi.org/10.1109/ICDE65706.2026.00139 | [
"Guofan Yu",
"Sitian Chen",
"Zhenheng Tang",
"Xiaowen Chu",
"Amelie Chi Zhou"
] | Full-graph GNN training delivers high accuracy but scales poorly on multi-server clusters due to heavy, irregular inter-node embedding exchanges. We present SNI-GNN, a SmartNIC-assisted full-graph training system that reduces communication while preserving accuracy by predicting remote embeddings in-network. SNI-GNN de... | # | ICDE2026 |
A Robust and Globally-Accurate Hierarchical Hub Labeling Index for SP-Distance Queries in Dynamic Road Networks | https://doi.org/10.1109/ICDE65706.2026.00140 | [
"Wei Liu",
"Ziqiang Yu",
"Xiaohui Yu",
"Yang Liu",
"Simu Liu"
] | Computing shortest-path distances between two points in road networks, typically modeled as dynamic weighted graphs due to fluctuating travel times, is fundamental to many location-based services demanding both accuracy and low latency. Existing hierarchical distance indexes for such graphs often face a trade-off: some... | # | ICDE2026 |
TRADER: Real-time Arbitrage Detection via Negative Cycles on Dynamic Graphs | https://doi.org/10.1109/ICDE65706.2026.00141 | [
"Bingqiao Luo",
"Yuhang Chen",
"Jiaxin Jiang",
"Yuheng Cong",
"Ziyu He",
"Shixuan Sun",
"Bingsheng He",
"Wee Howe Ang"
] | Real-time arbitrage detection in decentralized finance (DeFi) is challenging, as opportunities, which are often represented by negative cycles in token graphs, appear and disappear within milliseconds. High update rates and algorithmic complexity make real-time detection difficult, while existing approaches either oper... | # | ICDE2026 |
Decomposition-Driven Multi-Table Retrieval and Reasoning for Numerical Question Answering | https://doi.org/10.1109/ICDE65706.2026.00142 | [
"Feng Luo",
"Hai Lan",
"Hui Luo",
"Zhifeng Bao",
"Xiaoli Wang",
"J. Shane Culpepper",
"Shazia Sadiq"
] | In this paper, we study the problem of numerical multi-table question answering (MTQA) over large-scale table collections (e.g., online data repositories). This task is essential in many analytical applications. Existing MTQA solutions, such as text-to-SQL or open-domain MTQA methods, are designed for databases and str... | # | ICDE2026 |
HaS: Accelerating RAG Through Homology-Aware Speculative Retrieval | https://doi.org/10.1109/ICDE65706.2026.00143 | [
"Peng Peng",
"Weiwei Lin",
"Wentai Wu",
"Xinyang Wang",
"Yongheng Liu"
] | Retrieval-Augmented Generation (RAG) expands the knowledge boundary of large language models (LLMs) at inference by retrieving external documents as context. However, retrieval becomes increasingly time-consuming as the knowledge databases grow in size. Existing acceleration strategies either compromise accuracy throug... | https://github.com/ErrEqualsNil/HaS | ICDE2026 |
SaCal: An Efficient Saliency-Guided Causal Framework for Interpretable Healthcare Analytics | https://doi.org/10.1109/ICDE65706.2026.00144 | [
"Feixuan Lin",
"Chenyu You",
"Zhongle Xie",
"Zhaojing Luo",
"Meihui Zhang"
] | Multi-modal Electronic Health Records (EHRs) enable comprehensive patient assessment and facilitate multi-task prediction in healthcare. Current relevant studies mainly focus on three aspects: multi-modal learning (MML), multi-task learning (MTL), and multi-modal multi-task learning (MM-MTL). MML approaches attempt to ... | # | ICDE2026 |
BOND: A Co-Designed Framework for LLM-Powered Analytics Over Relational Data | https://doi.org/10.1109/ICDE65706.2026.00145 | [
"Lixiang Chen",
"Qin Zheng",
"Zhicheng Pan",
"Chengcheng Yang",
"Rong Zhang",
"Xuan Zhou"
] | The integration of Large Language Models (LLMs) into database systems through SQL has made the data analytics workflow elegant. However, this integration introduces significant computational overhead, as conventional LLM inference is not optimized for relational workloads. Existing optimization techniques are often des... | # | ICDE2026 |
Efficient Top-$k$ Nearest Neighbors Search in Dynamic Road Networks | https://doi.org/10.1109/ICDE65706.2026.00146 | [
"Junhua Zhang",
"Yamei Song",
"Wentao Li",
"Lu Qin"
] | Top-k Nearest Neighbors $(k \text{NN})$ search is a fundamental problem in road networks, which finds the $k$ nearest objects to a query point in the network and has numerous applications in location-based services. Existing solutions mainly focus on static road networks, they fail to address the dynamic nature of real... | # | ICDE2026 |
An Efficient and Scalable Approach for Path Queries on Public Transportation Networks | https://doi.org/10.1109/ICDE65706.2026.00147 | [
"Junhua Zhang",
"Wentao Li",
"Wenjie Zhang",
"Lu Qin",
"Xiaochun Yang"
] | Public transportation is crucial for mitigating environmental pollution and alleviating traffic congestion. As a fundamental problem in public transportation networks, path query aims to find the optimal path from a source vertex to a destination vertex. Several methods have been proposed to speed up the path queries b... | # | ICDE2026 |
Truth $\neq$ Frequency: Leveraging Dependencies for Subset Repair | https://doi.org/10.1109/ICDE65706.2026.00148 | [
"Haoda Li",
"Jiahui Chen",
"Yu Sun",
"Shaoxu Song",
"Haiwei Zhang",
"Xiaojie Yuan"
] | Inconsistent values are commonly encountered in real-world applications, which can negatively impact data analysis and decision-making. While existing research primarily focuses on identifying the smallest removal set to resolve inconsistencies, recent studies have shown that the minimum repairing principle is often in... | # | ICDE2026 |
iKSP: A Path Enumeration Index in Road Networks | https://doi.org/10.1109/ICDE65706.2026.00149 | [
"Zihan Luo",
"Lei Li",
"Mengxuan Zhang",
"Xinjie Zhou",
"Zizhuo Xu",
"Xiaofang Zhou"
] | Enumerating the top- $k$ simple shortest path (KSP) is a fundamental searching strategy for many path-related applications. However, the efficiency of current solutions is not acceptable, especially when the required $k$ is large, which becomes a bottleneck for many downstream tasks like Diversified KSP (DkSP) and Cons... | # | ICDE2026 |
Novel Table Search | https://doi.org/10.1109/ICDE65706.2026.00150 | [
"Besat Kassaie",
"Renée J. Miller"
] | Avoiding redundancy in query results has been extensively studied in relational databases and information retrieval, yet its implications for data lakes remain largely unexplored. We bridge this gap by investigating how to discover unionable tables that contribute new information for a given query table in large-scale ... | # | ICDE2026 |
Query-Guided Analysis and Mitigation of Data Verification Errors | https://doi.org/10.1109/ICDE65706.2026.00151 | [
"Ran Schreiber",
"Yael Amsterdamer"
] | Data verification, the process of labeling data items as correct or incorrect, is a preprocessing step that may critically affect the quality of results in data-driven pipelines. Despite recent advances, verification can still produce erroneous labels that propagate to downstream query results in complex ways. We prese... | # | ICDE2026 |
ImmortalChopper: Real-Time and Resilient Distributed Transactions in the Edge-Cloud | https://doi.org/10.1109/ICDE65706.2026.00152 | [
"Juncheng Fang",
"Farzad Habibi",
"Binbin Gu",
"Faisal Nawab"
] | Emerging applications in the areas of real-time Internet of Things (IoT) and edge technologies require fast processing and response times. This motivates the utilization of edge nodes for storing and processing data close to the user. In settings with a vast number of edge nodes, the state of the data is distributed ac... | # | ICDE2026 |
DIFFCOM: Conditional Discrete Diffusion Model for Community Search | https://doi.org/10.1109/ICDE65706.2026.00154 | [
"Ling Li",
"Liang Bai",
"Siqiang Luo",
"Yejiang Wang",
"Yuhai Zhao"
] | Learning-based community search methods have attracted widespread attention due to their effectiveness. Recently, continuous diffusion models have been introduced for community search, achieving strong performance. However, such continuous diffusion models may introduce boundary ambiguity, making it difficult to conver... | # | ICDE2026 |
GECO: A Confidentiality-Preserving and High-Performance Permissioned Blockchain Framework for General Smart Contracts | https://doi.org/10.1109/ICDE65706.2026.00155 | [
"Songxiao Guo",
"Rongxin Guan",
"Ji Qi",
"Zongyuan Zhang",
"Tianyang Duan",
"Sen Wang",
"Yanjun Wu",
"Heming Cui"
] | Data confidentiality is essential for blockchain applications that handle sensitive data. A promising approach to achieving data confidentiality is executing smart contracts on homomorphic encrypted ciphertext and then verifying correctness through non-interactive zero-knowledge proofs (NIZKPs). However, existing solut... | # | ICDE2026 |
Distance Comparison Operations are not Silver Bullets in Vector Similarity Search: A Benchmark Study on their Merits and Limits | https://doi.org/10.1109/ICDE65706.2026.00156 | [
"Zhuanglin Zheng",
"Yuxiang Zeng",
"Chenchen Liu",
"Yunzhen Chi",
"Binhan Yang",
"Yongxin Tong"
] | Distance Comparison Operations (DCOs), which decide whether the distance between a data vector and a query is within a threshold, are a critical performance bottleneck in vector similarity search. Recent DCO methods that avoid full-dimensional distance computations promise significant speedups, but their readiness for ... | # | ICDE2026 |
Efficient Community Search on Attributed Public-Private Graphs | https://doi.org/10.1109/ICDE65706.2026.00157 | [
"Yuqi Chen",
"Weihan Zhang",
"Xin Huang"
] | Public-private graph, where a public network is visible to everyone and every user is also associated with its own small private graph accessed by itself only, widely exists in realworld applications of social networks and financial networks. Most existing work on community search, finding a querydependent community co... | # | ICDE2026 |
Batcher: Learning to Construct Cost-Efficient Batches of Small Queries in Big Data Processing Platforms | https://doi.org/10.1109/ICDE65706.2026.00158 | [
"Yeonsu Park",
"Taesung Lee",
"Byungchul Tak",
"Wook-Shin Han"
] | Diverse big data processing platforms play critical roles in modern data analytics systems. Their strengths lie in processing queries on huge volumes of data with high parallelism on distributed nodes. However, one type of workload, made of an excessive number of small queries, is known to pose performance issues by pr... | # | ICDE2026 |
UTune: Towards Uncertainty-Aware Online Index Tuning | https://doi.org/10.1109/ICDE65706.2026.00160 | [
"Chenning Wu",
"Sifan Chen",
"Wentao Wu",
"Yinan Jing",
"Zhenying He",
"Kai Zhang",
"X. Sean Wang"
] | There have been a flurry of recent proposals on learned benefit estimators for index tuning. Although these learned estimators show promising improvement over what-if query optimizer calls in terms of the accuracy of estimated index benefit, they face significant limitations when applied to online index tuning, an argu... | # | ICDE2026 |
RAMSeS: Robust and Adaptive Model Selection for Time-Series Anomaly Detection Algorithms | https://doi.org/10.1109/ICDE65706.2026.00161 | [
"Mohamed Abdelmaksoud",
"Sheng Ding",
"Andrey Morozov",
"Ziawasch Abedjan"
] | Time-series data vary widely across domains, making a universal anomaly detector impractical. Methods that perform well on one dataset often fail to transfer because what counts as an anomaly is context dependent. The key challenge is to design a method that performs well in specific contexts while remaining adaptable ... | # | ICDE2026 |
CARROT: A Learned Cost-Constrained Retrieval Optimization System for RAG | https://doi.org/10.1109/ICDE65706.2026.00162 | [
"Ziting Wang",
"Haitao Yuan",
"Wei Dong",
"Gao Cong",
"Feifei Li"
] | Large Language Models (LLMs) have demonstrated impressive ability in generation and reasoning tasks but struggle with handling up-to-date knowledge, leading to inaccuracies or hallucinations. Retrieval-Augmented Generation (RAG) mitigates this by retrieving and incorporating external knowledge into input prompts. In pa... | https://github.com/wang0702/CARROT | ICDE2026 |
SLGParser: Practical and Efficient Label-Free Log Parsing Using Large Language Models | https://doi.org/10.1109/ICDE65706.2026.00163 | [
"Yibing Hu",
"Cong Wang",
"Lixin Zhao",
"Aimin Yu"
] | Logs serve as crucial artifacts for recording runtime system states and play a vital role in system diagnostics, security analysis, and performance optimization. Log parsing, the process of converting semi-structured logs into structured formats, is a pivotal preliminary step for enabling automated log analysis and uti... | # | ICDE2026 |
Unifying Graph Traversals and Time Series Joins in Hybrid Graphs | https://doi.org/10.1109/ICDE65706.2026.00164 | [
"Gianluca Rossi",
"Angela Bonifati",
"Riccardo Tommasini"
] | Graphs are highly expressive data structures for modelling and analysing relationships between real-world objects, with several applications, such as fraud detection, social and transportation networks. Traditionally, graphs and time series have been treated and studied as separate entities. However, the growing comple... | # | ICDE2026 |
RFOD: Random Forest-Based Outlier Detection for Mixed-Type Tabular Data | https://doi.org/10.1109/ICDE65706.2026.00165 | [
"Yihao Ang",
"Peicheng Yao",
"Yifan Bao",
"Yushuo Feng",
"Qiang Huang",
"Anthony K. H. Tung",
"Zhiyong Huang"
] | Outlier detection in tabular data is crucial for safeguarding data integrity in high-stakes domains such as cybersecurity, financial fraud detection, and healthcare, where anomalies can lead to severe operational and economic risks. Despite advances in both data mining and deep learning, existing methods often struggle... | https://github.com/YihaoAng/RFOD/ | ICDE2026 |
CAMMSR: Category-Guided Attentive Mixture of Experts for Multimodal Sequential Recommendation | https://doi.org/10.1109/ICDE65706.2026.00166 | [
"Jinfeng Xu",
"Zheyu Chen",
"Shuo Yang",
"Jinze Li",
"Hewei Wang",
"Yijie Li",
"Jianheng Tang",
"Yunhuai Liu",
"Edith C. H. Ngai"
] | The explosion of multimedia data in informationrich environments has intensified the challenges of personalized content discovery, positioning recommendation systems as an essential form of passive data management. Multimodal sequential recommendation, which leverages diverse item information such as text and images, h... | # | ICDE2026 |
CactusDB: Unlock Co-Optimization Opportunities for SQL Queries and AI/ML Model Inferences | https://doi.org/10.1109/ICDE65706.2026.00167 | [
"Lixi Zhou",
"Kanchan Chowdhury",
"Lulu Xie",
"Jaykumar Tandel",
"Hong Guan",
"Zhiwei Fan",
"Xinwei Fu",
"Jia Zou"
] | There is a growing demand for supporting inference queries that combine Structured Query Language (SQL) and Artificial Intelligence / Machine Learning (AI/ML) model inferences in database systems, to avoid data denormalization and transfer, facilitate management, and alleviate privacy concerns. Co-optimization techniqu... | # | ICDE2026 |
Time-Varying Vector Field Compression with Preserved Critical Point Trajectories | https://doi.org/10.1109/ICDE65706.2026.00168 | [
"Mingze Xia",
"Yuxiao Li",
"Pu Jiao",
"Bei Wang",
"Xin Liang",
"Hanqi Guo"
] | Scientific simulations and observations are generating massive volumes of time-varying vector field data, posing significant challenges for long-term storage and data transmission. Lossy compression is widely regarded as a promising approach for reducing data volume, as lossless methods typically achieve only modest co... | # | ICDE2026 |
Geography-Aware Large Language Models for Next POI Recommendation | https://doi.org/10.1109/ICDE65706.2026.00170 | [
"Wei Liu",
"Zhao Liu",
"Muzu Xie",
"Huaijie Zhu",
"Jianxing Yu",
"Jian Yin",
"Wang-Chien Lee"
] | The next Point-of-Interest (POI) recommendation task, which predicts a user's subsequent destination based on historical mobility data, is a key problem in location-based services and personalized data management. Accurate next POI recommendation requires effective modeling of geographic dependencies and collaborative ... | https://github.com/hugh2009hugh/GA-LLM | ICDE2026 |
Label-Constrained Column Annotation with Language Models and Graph Neural Networks | https://doi.org/10.1109/ICDE65706.2026.00171 | [
"Duo Yang",
"Ioannis Dasoulas",
"Anastasia Dimou"
] | Assigning semantic labels to table columns and identifying relations between columns pose significant challenges in data management. Automatic column annotation has been widely treated as classification, with recent works using language models trained on annotated tables with type and property labels. While these langu... | # | ICDE2026 |
When Complex Event Recognition Meets Cloud-Native Architectures | https://doi.org/10.1109/ICDE65706.2026.00172 | [
"Shizhe Liu",
"Haipeng Dai",
"Meng Li",
"Yuemeng Zhang",
"Shaoxu Song",
"Zhifeng Bao",
"Hancheng Wang",
"Xiaofeng Gao",
"Guihai Chen"
] | Complex Event Recognition (CER) aims to detect a predefined pattern composed of multiple primitive events. With the growing adoption of cloud-native techniques (i.e., computing and storage separation), which offer elasticity, availability, and cost efficiency, many database vendors are migrating their products to such ... | # | ICDE2026 |
ABC: Numerical Data Collection Under Local Differential Privacy Without Prior Knowledge | https://doi.org/10.1109/ICDE65706.2026.00174 | [
"Incheol Baek",
"Hyungbin Kim",
"Yon Dohn Chung"
] | Local Differential Privacy (LDP) provides strong privacy guarantees for collecting numerical data. A fundamental challenge, however, is that existing LDP mechanisms require a predefined data domain, which is often unknown in practice. This lack of prior knowledge creates a critical dilemma for the data collector: if th... | # | ICDE2026 |
REMON: Remote External Memory Over the Network | https://doi.org/10.1109/ICDE65706.2026.00175 | [
"Shiquan Zhang",
"Michail Bachras",
"Yuqiu Zhang",
"Yunhao Mao",
"Hans-Arno Jacobsen"
] | Modern database systems face significant challenges in managing memory efficiently, especially under conditions of resource heterogeneity, constrained local memory, and growing dataset sizes. To address these issues, we introduce REMON, a lightweight, software-based disaggregated memory system that leverages remote mem... | # | ICDE2026 |
Incremental GNN Embedding Computation on Streaming Graphs | https://doi.org/10.1109/ICDE65706.2026.00176 | [
"Qiange Wang",
"Haoran Lv",
"Yanfeng Zhang",
"Weng-Fai Wong",
"Bingsheng He"
] | Graph Neural Network (GNN) on streaming graphs has gained increasing popularity. However, its practical deployment remains challenging, as the inference process relies on Runtime Embedding Computation (RTEC) to capture recent graph changes. This process incurs heavyweight multi-hop graph traversal overhead, which signi... | # | ICDE2026 |
Lightweight 2-Hop Labels for Reachability Queries on Large-Scale Graphs | https://doi.org/10.1109/ICDE65706.2026.00177 | [
"Yishu Wang",
"Jinlong Chu",
"Ye Yuan",
"Yu Gu",
"Lianpeng Qiao"
] | Reachability queries are a fundamental problem in graph analysis. To avoid the high cost of traversal-based methods, indexing techniques have been widely studied, among which 2-hop labeling is particularly attractive due to its simplicity and query efficiency. However, maintaining reachability information for all verti... | # | ICDE2026 |
WikiDBGraph: A Data Management Benchmark Suite for Collaborative Learning Over Database Silos | https://doi.org/10.1109/ICDE65706.2026.00178 | [
"Zhaomin Wu",
"Ziyang Wang",
"Bingsheng He"
] | Relational databases are often fragmented across organizations, creating data silos that hinder distributed data management and mining. Collaborative learning (CL) -- techniques that enable multiple parties to train models jointly without sharing raw data -- offers a principled approach to this challenge. However, exis... | # | ICDE2026 |
Clue-RAG: Towards Accurate and Cost-Efficient Graph-Based RAG Via Multi-Partite Graph-Based Index | https://doi.org/10.1109/ICDE65706.2026.00179 | [
"Yaodong Su",
"Yixiang Fang",
"Yingli Zhou",
"Chuanhui Yang"
] | Despite the remarkable progress of Large Language Models (LLMs), their performance in question answering (QA) remains limited by the lack of domain-specific and up-to-date knowledge. Retrieval-Augmented Generation (RAG) addresses this limitation by incorporating external information, often from graph-structured data. H... | https://github.com/Feesuu/ClueRAG | ICDE2026 |
VIREO: Human-in-the-Loop DBMS Fuzzing with Visualization and LLM Support | https://doi.org/10.1109/ICDE65706.2026.00180 | [
"Jie Liang",
"Zhiyong Wu",
"Jingzhou Fu",
"Chi Zhang",
"Runpei Miao",
"Zhuo Su",
"Yu Jiang",
"Shuai Ma"
] | DBMSs are critical infrastructures that directly affect the security and correctness of many dependent applications. Recent advances in DBMS fuzzing have improved coverage and efficiency, discovering many bugs. However, in practice, many DBMS fuzzers explore only a limited state space, as many functionalities involve c... | # | ICDE2026 |
LEAF-SQL: Level-Wise Exploration with Adaptive Fine-Graining for Text-to-SQL Skeleton Prediction | https://doi.org/10.1109/ICDE65706.2026.00181 | [
"Zhao Tan",
"Xiping Liu",
"Qing Shu",
"Qizhi Wan",
"Dexi Liu",
"Changxuan Wan"
] | Text-to-SQL translates natural language questions into executable SQL queries, enabling intuitive database access for non-experts. While large language models achieve strong performance on Text-to-SQL with prompting, they still struggle with complex queries that involve deeply nested logic or multiple clauses. A widely... | # | ICDE2026 |
An Efficient and Effective Evaluator for Text2SQL Models on Unseen and Unlabeled Data | https://doi.org/10.1109/ICDE65706.2026.00182 | [
"Trinh Pham",
"Thanh Tam Nguyen",
"Viet Huynh",
"Hongzhi Yin",
"Quoc Viet Hung Nguyen"
] | Recent advances in large language models has strengthened Text2SQL systems that translate natural language questions into database queries. A persistent deployment challenge is to assess a newly trained Text2SQL system on an unseen and unlabeled dataset when no verified answers are available. This situation arises freq... | https://github.com/phkhanhtrinh23/FusionSQL | ICDE2026 |
PAT: Towards Transaction Routing with Page Affinity in Shared-Cache Databases | https://doi.org/10.1109/ICDE65706.2026.00184 | [
"Zhongqin Tan",
"Haoyuan Zhang",
"Yanfeng Zhang",
"Zeshun Peng",
"Weixing Zhou",
"Jinyu Zhang",
"Yang Ren",
"Guoliang Li",
"Ge Yu"
] | Shared-cache architectures decouple compute from storage and employ local caches in compute nodes to reduce the latency of accessing shared storage, achieving high availability and elasticity. However, this design suffers from local cache misses and cache coherence overhead. Transaction routing has been widely used to ... | # | ICDE2026 |
Density Decomposition of Multilayer Graphs | https://doi.org/10.1109/ICDE65706.2026.00185 | [
"Jiaqi Jiang",
"Rong-Hua Li",
"Yalong Zhang"
] | Multilayer graphs have emerged as a powerful model for representing complex systems with diverse types of interactions. Identifying cohesive subgraphs in such graphs is a fundamental task with broad applications in community detection, fraud analysis, and e-commerce recommendation. However, existing models either lack ... | # | ICDE2026 |
AOEH: An Efficient Extendable Hashing to Reduce Read/Write Amplification for Persistent Memory | https://doi.org/10.1109/ICDE65706.2026.00186 | [
"Shihao Zhang",
"Chi Zhang",
"Yunfei Gu",
"Chentao Wu",
"Jie Li",
"Junzhe Lv"
] | With the exponential growth of data volumes and index sizes, DRAM capacity has become a critical bottleneck in modern high-performance systems. Expanded memory architectures, particularly those leveraging Persistent Memory (PM), offer a promising solution by combining high capacity, byteaddressability, and non-volatile... | # | ICDE2026 |
Nezha: A Key-Value Separated Distributed Store with Optimized Raft Integration | https://doi.org/10.1109/ICDE65706.2026.00187 | [
"Yangyang Wang",
"Yucong Dong",
"Ziqian Cheng",
"Zichen Xu"
] | Distributed key-value stores are widely adopted to support elastic big data applications, leveraging purpose-built consensus algorithms like Raft to ensure data consistency. However, through systematic analysis, we reveal a critical performance issue in such consistent stores, i.e., overlapping persistence operations b... | # | ICDE2026 |
SpendableStore: A UTXO-Based Decentralized Data Store | https://doi.org/10.1109/ICDE65706.2026.00153 | [
"Yinan Zhou",
"Faisal Nawab"
] | The literature on blockchain-based databases is divided into permissioned blockchains and permissionless accountbased blockchains. However, the former is not fully decentralized, and the latter suffers from challenges in scalability and practicality. We propose SpendableStore, a hybrid on/off-chain database that operat... | # | ICDE2026 |
Process Faster, Pay Less: Functional Isolation for Stream Processing | https://doi.org/10.1109/ICDE65706.2026.00188 | [
"Eleni Zapridou",
"Michael Koepf",
"Panagiotis Sioulas",
"Ioannis Mytilinis",
"Anastasia Ailamaki"
] | Concurrent workloads often extract insights from high-throughput, real-time data streams. Existing stream processing engines isolate each query's resources, ensuring robust performance but incurring high infrastructure costs. In contrast, sharing work reduces the amount of necessary resources but introduces inter-query... | # | ICDE2026 |
SQAC: Scalable Querying of Attribute-Constrained (α, β)-Cores over Large Bipartite Graphs | https://doi.org/10.1109/ICDE65706.2026.00189 | [
"Xin Deng",
"Peng Peng",
"Baoqing Sun",
"Shuo Dai",
"Zheng Qin",
"Lijun Chang"
] | Many important real-world networks can be effectively modeled as bipartite graphs, where vertex attributes convey critical semantic information essential for graph analysis. As a fundamental subgraph structure in bipartite graphs, (α, β)-cores have attracted extensive attention and been widely used. However, existing s... | # | ICDE2026 |
Listing Minimal Cores in Large Real-World Graphs | https://doi.org/10.1109/ICDE65706.2026.00190 | [
"Yukai Sun",
"Kaiqiang Yu",
"Shengxin Liu",
"Cheng Long",
"Raymond Chi-Wing Wong",
"Xun Zhou",
"Min Zhang"
] | Cohesive subgraph mining is a fundamental task in graph data analytics. We re-visit the problem of listing all minimal $k$-cores, where a $k$-core is a subgraph in which every vertex has degree at least $k$, and minimality requires that no proper subset remains a $k$-core. Existing methods are computationally prohibiti... | # | ICDE2026 |
Time-Frequency Conditioned Diffusion for Multivariate Time Series Imputation | https://doi.org/10.1109/ICDE65706.2026.00191 | [
"Yumeng Liu",
"Zheng Wang",
"Jikui Liu",
"Kaisa Zhang",
"Weidong Gao",
"Xiaomao Fan"
] | Time series data underpin critical applications in domains including healthcare and meteorology, yet their utility is frequently compromised by pervasive missing values. While diffusion-based generative models offer promise for imputation, existing approaches are constrained by their limited ability to effectively capt... | https://github.com/Cofeesy/CDTI | ICDE2026 |
Low-Latency Stateful Stream Processing Through Timely and Accurate Prefetching | https://doi.org/10.1109/ICDE65706.2026.00192 | [
"Eleni Zapridou",
"Anastasia Ailamaki"
] | Mission-critical applications often run “forever” and process large data volumes in real time while demanding low latency. To handle the large state of these applications, modern streaming engines rely on key-value stores and store state on local storage or remotely, but accessing such state inflates latency. As today'... | # | ICDE2026 |
Hydra: Breaking the Global Ordering Barrier in Multi-BFT Consensus | https://doi.org/10.1109/ICDE65706.2026.00193 | [
"Hanzheng Lyu",
"Shaokang Xie",
"Jianyu Niu",
"Mohammad Sadoghi",
"Yinqian Zhang",
"Cong Wang",
"Ivan Beschastnikh",
"Chen Feng"
] | Multi-Byzantine Fault Tolerant (Multi-BFT) consensus, which runs multiple BFT instances in parallel, has recently emerged as a promising approach to overcome the leader bottleneck in classical BFT protocols. However, existing designs rely on a global ordering layer to serialize blocks across instances, an intuitive yet... | # | ICDE2026 |
Rangereduce: Query-Driven LSM Compactions | https://doi.org/10.1109/ICDE65706.2026.00194 | [
"Shubham Kaushik",
"Manos Athanassoulis",
"Subhadeep Sarkar"
] | Log-structured merge (LSM) trees are widely used in the storage layer of modern ingestion-optimized data stores. The high ingestion throughput, however, comes at the cost of sub-optimal range query (RQ) performance. This is because LSM-trees arrange the data as a hierarchical collection of sorted runs, which implies th... | # | ICDE2026 |
F5: A Robust SIMD-Accelerated MSD Radix Sort | https://doi.org/10.1109/ICDE65706.2026.00195 | [
"Arif Arman",
"Dmitri Loguinov"
] | Sorting is a building block of many data-intensive applications, databases, MapReduce pipelines, and large-scale distributed systems. In this paper, we focus on MSD (mostsignificant digit first) radix sort, in which we identify three main bottlenecks - slow small-bucket sorts at the end of recursion, partitioning algor... | # | ICDE2026 |
SQLMorph: Query Mutation and Fine-Grained Metrics for Text-to-SQL Evaluation | https://doi.org/10.1109/ICDE65706.2026.00196 | [
"Mohammadhossein Malekpour",
"Mohamed Riahi",
"Maxime Lamothe",
"Amine Mhedhbi"
] | Text-to-SQL systems translate natural language queries into executable SQL, democratizing access to structured data. Despite recent advances driven by large language models (LLMs), evaluation remains a major bottleneck: public benchmarks fail to capture the complexity of enterprise schema, while building private evalua... | # | ICDE2026 |
Telescope: A Learned What-If Call for Column Store Selection in HTAP Databases | https://doi.org/10.1109/ICDE65706.2026.00197 | [
"Yidong Zhang",
"Chao Zhang",
"Zhengkun Wu",
"Ju Fan",
"Xinyi Zhang",
"Hong Chen",
"Yuxing Chen",
"Anqun Pan"
] | Recently, we have witnessed that various HTAP databases have integrated the primary row store with an inmemory column store to benefit from both storage engines, i.e., row store for OLTP and column store for OLAP. Nevertheless, existing systems cannot evaluate the true benefit of the column store on query processing wi... | # | ICDE2026 |
TORepair: Diffusion-Based Task-Oriented Error Repair Via Differentiable Bi-Level Optimization | https://doi.org/10.1109/ICDE65706.2026.00198 | [
"Wei Ni",
"Xiaoye Miao",
"Xiangyu Zhao",
"Yangyang Wu",
"Jianwei Yin"
] | Error repair in tabular data is crucial for downstream task utility. Existing methods either pursue data fidelity, potentially degrading task performance, or are task-oriented but require manual effort or extensive retraining, while lacking theoretical guarantees. In this paper, we propose TORepair, a novel framework t... | # | ICDE2026 |
Table Question Answering via Adaptive Routing | https://doi.org/10.1109/ICDE65706.2026.00199 | [
"Yang Liu",
"Mengyi Yan",
"Jiao Xue",
"Weilong Ren",
"Yutong Ye",
"Haoyi Zhou",
"Jianxin Li",
"Zhumin Chen"
] | Table Question Answering (TQA), which aims to answer natural language questions over tabular data, has recently attracted growing interest in the database community. While state-of-the-art (SOTA) methods based on online Large Language Models (LLMs) achieve remarkable accuracy, they suffer from several drawbacks, includ... | https://github.com/authurlord/SPARQ | ICDE2026 |
[Experiment, Analysis, and Benchmark] BEACON: A Benchmark for Efficient and Accurate Counting of Subgraphs | https://doi.org/10.1109/ICDE65706.2026.00200 | [
"Xiangju Zhu",
"Mohammad Matin Najafi",
"Chrysanthi Kosyfaki",
"Xiaodong Li",
"Reynold Cheng",
"Laks V. S. Lakshmanan"
] | Subgraph counting, the task of determining the number of instances of a query pattern within a large graph, plays an important role in many real-world applications, from analyzing financial networks and transportation systems to understanding biological interactions. Although this problem has been widely explored, rang... | # | ICDE2026 |
XRAG: Examining the Core - Benchmarking Foundational Components in Advanced Retrieval-Augmented Generation | https://doi.org/10.1109/ICDE65706.2026.00201 | [
"Qili Zhang",
"Qianren Mao",
"Yangyifei Luo",
"Yashuo Luo",
"Hanwen Hao",
"Zhilong Cao",
"Weifeng Jiang",
"Zhijun Chen",
"Junnan Liu",
"Feng Yan",
"Xiaolong Wang",
"Jinlong Zhang",
"Zhenting Huang",
"Zhixing Tan",
"Jie Sun",
"Bo Li",
"Jianxin Li",
"Philip S. Yu"
] | Retrieval-augmented generation (RAG) synergizes the retrieval of pertinent data with the generative capabilities of Large Language Models (LLMs), ensuring that the generated output is not only contextually relevant but also accurate and current. We introduce XRAG, an open-source, modular codebase that facilitates exhau... | # | ICDE2026 |
A-Scan: Efficient Scale-Up Analytics via Throughput-Guided Data Movement | https://doi.org/10.1109/ICDE65706.2026.00202 | [
"Hamish Nicholson",
"Aunn Raza",
"Viktor Sanca",
"Anastasia Ailamaki"
] | Modern scale-up analytical systems, from single servers to rack-scale deployments, face increasing complexity in data movement across their storage hierarchies, NUMA nodes, and high-speed interconnects like CXL and PCIe. The performance gap between optimal and suboptimal data-movement strategies can be substantial, as ... | # | ICDE2026 |
C2TC: A Training-Free Framework for Efficient Tabular Data Condensation | https://doi.org/10.1109/ICDE65706.2026.00203 | [
"Sijia Xu",
"Fan Li",
"Xiaoyang Wang",
"Zhengyi Yang",
"Xuemin Lin"
] | Tabular data, organized in rows and columns, represents the most common data format in industrial relational databases, underpinning modern data analytics and decisionmaking. However, the ever-increasing scale of tabular data poses significant computational and storage challenges to learningbased analytical systems. Th... | # | ICDE2026 |
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