4 papers
Reasoning Fine-Tuning Induces Persistent Latent Policy States
Abir Harrasse, Michael Lan, Hunar Batra +2
Reasoning-specialized language models show large performance gains over base models, yet the internal changes responsible for improved multi-step reasoning remain poorly understood…
Teaching People LLM's Errors and Getting it Right
Nathan Stringham, Fateme Hashemi Chaleshtori, Xinyuan Yan +3
People use large language models (LLMs) when they should not. This is partly because they see LLMs compose poems and answer intricate questions, so they understandably, but incorre…
Measuring Chain of Thought Faithfulness by Unlearning Reasoning Steps
Martin Tutek, Fateme Hashemi Chaleshtori, Ana MarasoviÄ +1
When prompted to think step-by-step, language models (LMs) produce a chain of thought (CoT), a sequence of reasoning steps that the model supposedly used to produce its prediction.…
BriefMe: A Legal NLP Benchmark for Assisting with Legal Briefs
Jesse Woo, Fateme Hashemi Chaleshtori, Ana MarasoviÄ +1
A core part of legal work that has been under-explored in Legal NLP is the writing and editing of legal briefs. This requires not only a thorough understanding of the law of a juri…