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Jie Yuan

Iowa State University

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Preprint Oct 2026

Learning Multi-Step Query Rewriting via Corpus Feedback for Conversational Search

Conversational Query Rewriting (CQR) turns a context dependent user turn into a standalone query for a retriever, and most methods do this in a single step from the dialogue history before retrieving once. The rewrite is therefore fixed before any corpus evidence is available to correct its reference resolution or its...

João Coelho, Hong Wang, Jie Yuan et al. · 0 citations
#machine learning Preprint Sep 2026

Giving Credit Where It's Due: Redundancy-Aware Learning for Efficient Reasoning

This work introduces RECAP (REdundancy-aware Credit Assignment via Propagation), which addresses this limitation by assigning credit where it is due based on both a step's downstream role in the reasoning structure and its contribution to solving the problem correctly.

Yu-Qing Zhou, Hong Wang, Man-Qing Mao et al. · 0 citations
#natural language process... Preprint Sep 2026

Local Edits, Global Ripples: Replay-Informed Policy Adaptation for Workflow Synthesis

RIPPLE (Replay-Informed Persistent Policy Localization and Editing), which separates where an edit is made from whether it remains safe to persist after composition, and improves validation success by up to 23.1% and yields positive gains on two additional frozen language-model backbones, while maintaining edit efficie...

Man-Qing Mao, Hong Wang, Samson Koelle et al. · 0 citations
Preprint Aug 2026

Optimizing What Policies Learn From: Recoverability-aware Rollout Intervention Learning

Recoverability-Aware Intervention Learning (RAIL), a training-time framework that learns how to generate rollouts based on the improvement produced by each intervention, consistently improves performance under limited rollout budgets.

Zheyuan Zhang, Man-Qing Mao, Hong Wang et al. · 0 citations

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