Get Started
Home
Topics
Search
Library
Research questionHow can reinforcement learning give LLMs useful intermediate feedback when rewards reveal only final correctness?A final outcome reward does not indicate which step in a reasoning trace first failed. Once a trace follows an invalid prefix, later reasoning provides limited diagnostic information about the original error.
AI
LLM Pretraining & Post-training
Machine Learning
Reasoning
Reinforcement Learning
Latest papersRecent research connected to this question, newest first.Cliff: Learning Process Rewards from the First MistakeThis concerns RLVR post-training for LLM reasoning, using an off-the-shelf LLM teacher to identify the first mistake in each rollout and assign token-level feedback to the correct prefix and incorrect suffix. Evidence covers 12 scenarios and comparisons with on-policy distillation and standard GRPO, including teachers of modest capability.research paper · Sep 2, 2026
Related questions
How can multi-turn LLM tutors personalize progressive guidance while preserving answer correctness?How can on-policy LLM reasoning turn unreliable skill-derived signals into reliable token-level supervision?Should reasoning LLMs combine on-policy distillation and verifiable-reward RL jointly or sequentially during post-training?How can we evaluate LLM reasoning quality beyond final-answer accuracy across deployment contexts?