In the news
Legibility is Not Interpretability: Comparing Judged and Actual Importance in Chain-Of-Thought Reasoning
arXiv cs.AI · Published · 3 min read
In 30 seconds
- What happened
- Researchers found that chain-of-thought reasoning text appears legible but doesn't reliably encode which steps actually matter for model decisions.
- Why it matters
- Matters for engineers building process reward models, using LLM judges for step-level supervision, or relying on reasoning traces for model diagnostics.
- Watch out
- LLM judges fall short of identifying truly important reasoning steps, especially for correct responses, suggesting interpretability claims about reasoning traces need caution.
- llm
- reasoning
- eval
- interpretability
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