On the effectiveness of reward functions in reinforcement learning for confidence calibration of large language models
cs.LG
Submitted: 2026-07-05
Updated: 2026-10-06
Code: https://github.com/mangiucugna/json_
Terminology
Sources
- GPT-4 Technical Report
- Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
- Uncalibrated Reasoning: GRPO Induces Overconfidence for Stochastic Outcomes
- Trace Length is a Simple Uncertainty Signal in Reasoning Models
- Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers
- Gemma 4 Technical Report
- The Llama 3 Herd of Models
- On Calibration of Modern Neural Networks
- DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning
- LoRA: Low-Rank Adaptation of Large Language Models
- Consistency of Large Reasoning Models Under Multi-Turn Attacks
- Understanding R1-Zero-Like Training: A Critical Perspective
- gpt-oss-120b & gpt-oss-20b Model Card
- Defeating the Training-Inference Mismatch via FP16
- Qwen3 Technical Report
- DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
- SCOPE-RL: Stable and Quantitative Control of Policy Entropy in RL Post-Training
- Mitigating LLM Hallucination via Behaviorally Calibrated Reinforcement Learning
- BAS: A Decision-Theoretic Approach to Evaluating Large Language Model Confidence
- It Takes Two: Your GRPO Is Secretly DPO
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