REWIND: Uncertainty-Guided Trajectory Repair for Test-Time Reasoning
cs.CL, cs.AI
Submitted: 2026-10-14
Updated: 2026-10-14
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs
- Evaluating Large Language Models Trained on Code
- Training Verifiers to Solve Math Word Problems
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- Measuring Mathematical Problem Solving With the MATH Dataset
- Large Language Models Cannot Self-Correct Reasoning Yet
- Language Models (Mostly) Know What They Know
- Reasoning with Sampling: Your Base Model is Smarter Than You Think
- Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation
- Tulu 3: Pushing Frontiers in Open Language Model Post-Training
- Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
- An Explanation of In-context Learning as Implicit Bayesian Inference
- Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
- Entropy-based Exploration Conduction for Multi-step Reasoning
- Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models
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