ملف الباحث

Ethan Mendes

ورقة واحدة في مجموعة PaperMetrix

المنشورات

أوراق هذا المؤلف

  1. Language Models can Self-Improve at State-Value Estimation for Better Search

    2025

    Collecting ground-truth rewards or human demonstrations for multi-step reasoning tasks is often prohibitively expensive, particularly in interactive domains such as web tasks. We introduce Self-Taught Lookahead (STL), a reward-free framework that improves language model-based value …