Collections
Discover the best community collections!
Collections including paper arxiv:2512.16301
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TradingAgents: Multi-Agents LLM Financial Trading Framework
Paper • 2412.20138 • Published • 49 -
Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing
Paper • 2509.08721 • Published • 665 -
From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence
Paper • 2511.18538 • Published • 304 -
Memory in the Age of AI Agents
Paper • 2512.13564 • Published • 157
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Agentic Reasoning for Large Language Models
Paper • 2601.12538 • Published • 204 -
From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence
Paper • 2511.18538 • Published • 304 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 277 -
Weak-Driven Learning: How Weak Agents make Strong Agents Stronger
Paper • 2602.08222 • Published • 290
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Attention Is All You Need
Paper • 1706.03762 • Published • 121 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 10 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 11 -
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
Paper • 2210.04186 • Published
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Adaptation of Agentic AI
Paper • 2512.16301 • Published • 108 -
Deep Research: A Systematic Survey
Paper • 2512.02038 • Published • 73 -
Scaling Agent Learning via Experience Synthesis
Paper • 2511.03773 • Published • 83 -
ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration
Paper • 2511.21689 • Published • 126
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O-Mem: Omni Memory System for Personalized, Long Horizon, Self-Evolving Agents
Paper • 2511.13593 • Published • 28 -
OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Paper • 2511.16931 • Published • 8 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 170 -
MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling
Paper • 2511.11793 • Published • 195
-
Agentic Reasoning for Large Language Models
Paper • 2601.12538 • Published • 204 -
From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence
Paper • 2511.18538 • Published • 304 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 277 -
Weak-Driven Learning: How Weak Agents make Strong Agents Stronger
Paper • 2602.08222 • Published • 290
-
Attention Is All You Need
Paper • 1706.03762 • Published • 121 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 10 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 11 -
Analogy Generation by Prompting Large Language Models: A Case Study of InstructGPT
Paper • 2210.04186 • Published
-
TradingAgents: Multi-Agents LLM Financial Trading Framework
Paper • 2412.20138 • Published • 49 -
Sharing is Caring: Efficient LM Post-Training with Collective RL Experience Sharing
Paper • 2509.08721 • Published • 665 -
From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence
Paper • 2511.18538 • Published • 304 -
Memory in the Age of AI Agents
Paper • 2512.13564 • Published • 157
-
Adaptation of Agentic AI
Paper • 2512.16301 • Published • 108 -
Deep Research: A Systematic Survey
Paper • 2512.02038 • Published • 73 -
Scaling Agent Learning via Experience Synthesis
Paper • 2511.03773 • Published • 83 -
ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestration
Paper • 2511.21689 • Published • 126
-
O-Mem: Omni Memory System for Personalized, Long Horizon, Self-Evolving Agents
Paper • 2511.13593 • Published • 28 -
OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Paper • 2511.16931 • Published • 8 -
General Agentic Memory Via Deep Research
Paper • 2511.18423 • Published • 170 -
MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling
Paper • 2511.11793 • Published • 195