TGRL: Temperature-Grouped Reinforcement Learning for Efficient Exploration in LLMs
cs.LG, cs.CL
Submitted: 2026-09-27
Updated: 2026-09-27
Code: https://github.com/1229095296/TGRL
Terminology
Sources
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning
- The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models
- Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models
- When Self-Belief Misleads: Active Label Acquisition for Reinforcement Learning with Verifiable Rewards
- ZipRL: Adaptive Multi-Turn Context Compression with Hindsight Response Replay
- Self-Consistency Improves Chain of Thought Reasoning in Language Models
- Large Language Monkeys: Scaling Inference Compute with Repeated Sampling
- Let it Calm: Exploratory Annealed Decoding for Verifiable Reinforcement Learning
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- Contextual Rollout Bandits for Reinforcement Learning with Verifiable Rewards
- Your Group-Relative Advantage Is Biased
- Understanding R1-Zero-Like Training: A Critical Perspective
- VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks
- DAPO: An Open-Source LLM Reinforcement Learning System at Scale
- Group Sequence Policy Optimization
- Parameter Space Noise for Exploration
- Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters
- Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning
- DRA-GRPO: Your GRPO Needs to Know Diverse Reasoning Paths for Mathematical Reasoning
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