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Puxuan Yu

2 accepted papers

2025

Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMs

ACL 2025finding

In search settings, calibrating the scores during the ranking process to quantities such as click-through rates or relevance levels enhances a system’s usefulness and trustworthiness for downstream users. While previous research has improved this notion of calibration for low complexity learning-to-…

2024

Language Concept Erasure for Language-invariant Dense Retrieval

EMNLP 2024main

Multilingual models aim for language-invariant representations but still prominently encode language identity. This, along with the scarcity of high-quality parallel retrieval data, limits their performance in retrieval. We introduce LANCER, a multi-task learning framework that improves language-inv…

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