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Towards Disentangling Relevance and Bias in Unbiased Learning to Rank


Dec 28, 2022
Yunan Zhang, Le Yan, Zhen Qin, Honglei Zhuang, Jiaming Shen, Xuanhui Wang, Michael Bendersky, Marc Najork

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What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis


Dec 21, 2022
Xiang Deng, Vasilisa Bashlovkina, Feng Han, Simon Baumgartner, Michael Bendersky

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Learning List-Level Domain-Invariant Representations for Ranking


Dec 21, 2022
Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky

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Regression Compatible Listwise Objectives for Calibrated Ranking


Nov 02, 2022
Aijun Bai, Rolf Jagerman, Zhen Qin, Pratyush Kar, Bing-Rong Lin, Xuanhui Wang, Michael Bendersky, Marc Najork

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RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses


Oct 12, 2022
Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, Michael Bendersky

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* 13 pages 

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Retrieval-Enhanced Machine Learning


May 02, 2022
Hamed Zamani, Fernando Diaz, Mostafa Dehghani, Donald Metzler, Michael Bendersky

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* To appear in proceedings of ACM SIGIR 2022 

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Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models


Jan 25, 2022
Tao Chen, Mingyang Zhang, Jing Lu, Michael Bendersky, Marc Najork

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* Accepted at ECIR 2022 (full paper) 

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Rank4Class: A Ranking Formulation for Multiclass Classification


Dec 17, 2021
Nan Wang, Zhen Qin, Le Yan, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork

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Born Again Neural Rankers


Sep 30, 2021
Zhen Qin, Le Yan, Yi Tay, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork

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Dynamic Language Models for Continuously Evolving Content


Jun 11, 2021
Spurthi Amba Hombaiah, Tao Chen, Mingyang Zhang, Michael Bendersky, Marc Najork

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* KDD 2021 

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