Papers by Yuning Wan

2 papers
Align Documents to Questions: Question-Oriented Document Rewriting for Retrieval-Augmented Generation (2026.findings-acl)

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Challenge: Retrieval-Augmented Generation (RAG) enhances the factuality of Large Language Models (LLMs) however, LLMs exhibit a stylistic bias when presented with mixed contexts, revealing a bottleneck in their utility.
Approach: They propose a style-controlled rewriter that aligns retrieved documents with a question-oriented style while preserving facts.
Outcome: The proposed model improves RAG pipelines by 8% with negligible latency overhead.
Knowledge Control for Responsible Generative AI: Bridging Academia, Industry, and Society (2026.acl-tutorials)

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Challenge: This tutorial introduces the foundations of post-training knowledge control and showcases recent frontier methods.
Approach: This tutorial introduces the foundations of post-training knowledge control and showcases recent frontier methods.
Outcome: This tutorial introduces the foundations of post-training knowledge control and showcases recent frontier methods . key motivations and failure modes, harmful generation and stereotype reinforcement, are addressed . core methods such as machine unlearning, knowledge editing, and inference-time interventions are also included .

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