Category: Reinforcement Learning

• Abandoning Manual Annotation! Chinese Team Proposes Self-Evolution Algorithm for Multimodal Large Models
• First Multi-Round LLM Router Unveiled: Router-R1 Teaches Large Models to "Think–Route–Aggregate"
• Princeton Danqi Chen's Group's New Work: RLHF Insufficient, RLVR Bounded? RLMT Forges a Third Path
• ByteDance Breaks the 'Entropy Curse' in LLM RL Training, Enabling Models to Learn with Certainty!
• Stanford Proposes New RL Paradigm: 3B Model Agent Outperforms Claude, GPT-4
• Microsoft Introduces rStar2-Agent: "Thinking Smarter" Proves Far More Effective and Efficient Than Simply "Thinking Longer"
• LLMs Dominate Math Boards, Yet Forget How to Chat? CMU et al. Reveal Striking Differences Between SFT and RL!
• Evolution and Development Trends of Reinforcement Learning Frameworks
• Advancing Silicon-Based Intelligence: Shuchao Bi's Insights on Past, Present, and Future AI
• ARPO: Agentic Reinforced Policy Optimization, Enabling Agents to Explore One Step Further at Critical Moments
• RAG Revolution! Graph-R1, the First RL-driven Graph Reasoning Agent
• Revisiting Qwen3's Abandoned Mixed Inference Mode
• Why Can't Language Models Directly Output Answers with Confidence?
• DeepSeek-GRPO Importance Weight Design Flaw? Explaining Qwen3's New Reinforcement Learning Algorithm GSPO
• Counter-Intuitive RL Research: Directly Providing Answers to LLMs is More Effective Than Detailed Step-by-Step Instructions!
• Alibaba Open-Sources Breakthrough Agent Overnight, Directly Challenges OpenAI with State-of-the-Art Performance!
• RL Scaling Breakthrough! DeepSWE Open-Source AI Agent Tops Leaderboard, Training Methods and Weights Fully Released
• Tsinghua Research: A Reversal? Confirming RL Doesn't Truly Enhance Base Model Reasoning Ability!
• Tsinghua and Others Propose Absolute Zero Self-Play Large Models, Achieving Top Performance on Multiple Tasks with Zero-Data Training
• AGI Theory Comparison: Active Inference, Reinforcement Learning, Control Theory, Bayesian Brain, Utility Decision, Bounded Rationality, Emotional Motivation, Dynamic Homeostasis
• LLMs Can Now Self-Update Weights, Significantly Enhancing Self-Adaptation and Knowledge Integration Capabilities – Has AI Awakened?
• NVIDIA (ProRL) | Can RL truly enhance the reasoning capabilities of LLMs?
• LLMs Can Now Self-Update Weights, Significantly Boosting Adaptive and Knowledge Integration Capabilities. Is AI Waking Up?
• SRO Architecture Empowers Qwen-2.5-VL's Reasoning Capability, Boosting Performance by 16.8%
• New Breakthrough in Large Model Reinforcement Learning – SPO New Paradigm Boosts Large Model Reasoning Capability!