Papers by Tang Biao

2 papers
ReList: A Multi-objective Reasoning Framework for Diversified Listwise Query Recommendation (2026.acl-industry)

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Challenge: Existing methods for related search have limited semantic redundancy and wasted retrieval quota . generative retrieval approaches lack explicit reasoning, relying on superficial click-through rate rewards .
Approach: They propose a framework that transforms related search into a reasoning-enhanced listwise generation task.
Outcome: Experimental results show that ReList outperforms state-of-the-art methods in query diversity and user engagement.
Consistency-Aware Online Multi-Objective Alignment for Related Search Query Generation (2025.acl-industry)

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Challenge: Existing methods fail to reconcile click-through rate (CTR) optimization with topic expansion.
Approach: They propose a query generation framework that aligns click-through rate and topic expansion goals through an online DPO paradigm.
Outcome: The proposed approach achieves significant CTR gains (+2.3%) and higher human-rated query quality compared to state-of-the-art methods.

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