ملف الباحث
Ethan Mendes
ورقة واحدة في مجموعة PaperMetrix
المنشورات
أوراق هذا المؤلف
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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 …