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S. Sarwar

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Preprint Aug 2026

Ask to Be Sure: Informative Interactions for Confident Multi-Turn LLM Recommendation

This work proposes a new approach that quantifies the effectiveness of each interaction by the reduction in the assistant's uncertainty, measured via entropy over recommendations, to fine-tune the LLM, enabling strategic interaction generation.

Cedar Site Bai, Zhenyu Liao, Duan Li et al. · 0 citations
#machine learning Preprint Aug 2026

Scaling Automatic Research Agents via World Models

This paper proposes World Model RL (WMRL), which replaces environment execution with a world model to remove this bottleneck and accelerates training by 3-4x on various tasks at different agent scales, while exceeding the performance of standard RL baselines.

Xi-Yuan Yang, S. Sarwar, Jingru Cheng et al. · 0 citations

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