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ORCIDKai Hui 0001
Person information
- affiliation: Google Research
- affiliation: Max Planck Institute for Informatics
- affiliation: Graduate University of the Chinese Academy of Sciences
Other persons with the same name
- Kai Hui 0002 — Northwest Institute of Mechanical & Electrical Engineering, Xianyang, China
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2020 – today
- 2024
[c38]Honglei Zhuang, Zhen Qin, Kai Hui, Junru Wu, Le Yan, Xuanhui Wang, Michael Bendersky:
Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels. NAACL (Short Papers) 2024: 358-370- [c37]Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Le Yan, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, Michael Bendersky:
Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting. NAACL-HLT (Findings) 2024: 1504-1518 - [c36]Minghan Li
, Honglei Zhuang, Kai Hui, Zhen Qin, Jimmy Lin, Rolf Jagerman, Xuanhui Wang, Michael Bendersky:
Can Query Expansion Improve Generalization of Strong Cross-Encoder Rankers? SIGIR 2024: 2321-2326 - [i26]Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, Blair Chen, Daniel Cer, Jeremy R. Cole, Kai Hui, Michael Boratko, Rajvi Kapadia, Wen Ding, Yi Luan, Sai Meher Karthik Duddu, Gustavo Hernández Ábrego, Weiqiang Shi, Nithi Gupta, Aditya Kusupati, Prateek Jain, Siddhartha Reddy Jonnalagadda, Ming-Wei Chang, Iftekhar Naim:
Gecko: Versatile Text Embeddings Distilled from Large Language Models. CoRR abs/2403.20327 (2024) - [i25]Zhenrui Yue, Honglei Zhuang, Aijun Bai, Kai Hui, Rolf Jagerman, Hansi Zeng, Zhen Qin, Dong Wang, Xuanhui Wang, Michael Bendersky:
Inference Scaling for Long-Context Retrieval Augmented Generation. CoRR abs/2410.04343 (2024) - 2023
- [j4]Xuanang Chen, Ben He, Kai Hui, Le Sun, Yingfei Sun:
Dealing with textual noise for robust and effective BERT re-ranking. Inf. Process. Manag. 60(1): 103135 (2023) - [c35]Ronak Pradeep, Kai Hui, Jai Gupta, Ádám D. Lelkes, Honglei Zhuang, Jimmy Lin, Donald Metzler, Vinh Q. Tran:
How Does Generative Retrieval Scale to Millions of Passages? EMNLP 2023: 1305-1321 - [c34]Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, Kai Hui:
PaRaDe: Passage Ranking using Demonstrations with LLMs. EMNLP (Findings) 2023: 14242-14252 - [c33]Zhen Qin, Rolf Jagerman, Rama Kumar Pasumarthi, Honglei Zhuang, He Zhang, Aijun Bai, Kai Hui, Le Yan, Xuanhui Wang:
RD-Suite: A Benchmark for Ranking Distillation. NeurIPS 2023 - [c32]Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky:
Learning List-Level Domain-Invariant Representations for Ranking. NeurIPS 2023 - [c31]Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, Michael Bendersky:
RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses. SIGIR 2023: 2308-2313 - [i24]Ronak Pradeep, Kai Hui, Jai Gupta, Ádám Dániel Lelkes, Honglei Zhuang, Jimmy Lin, Donald Metzler, Vinh Q. Tran:
How Does Generative Retrieval Scale to Millions of Passages? CoRR abs/2305.11841 (2023) - [i23]Zhen Qin, Rolf Jagerman, Rama Kumar Pasumarthi, Honglei Zhuang, He Zhang, Aijun Bai, Kai Hui, Le Yan, Xuanhui Wang:
RD-Suite: A Benchmark for Ranking Distillation. CoRR abs/2306.04455 (2023) - [i22]Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, Michael Bendersky:
Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting. CoRR abs/2306.17563 (2023) - [i21]Honglei Zhuang, Zhen Qin, Kai Hui, Junru Wu, Le Yan, Xuanhui Wang, Michael Bendersky:
Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels. CoRR abs/2310.14122 (2023) - [i20]Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, Kai Hui:
PaRaDe: Passage Ranking using Demonstrations with Large Language Models. CoRR abs/2310.14408 (2023) - [i19]Minghan Li, Honglei Zhuang, Kai Hui, Zhen Qin, Jimmy Lin, Rolf Jagerman, Xuanhui Wang, Michael Bendersky:
Generate, Filter, and Fuse: Query Expansion via Multi-Step Keyword Generation for Zero-Shot Neural Rankers. CoRR abs/2311.09175 (2023) - 2022
- [c30]Kai Hui, Honglei Zhuang, Tao Chen, Zhen Qin, Jing Lu, Dara Bahri, Ji Ma, Jai Prakash Gupta, Cícero Nogueira dos Santos, Yi Tay, Donald Metzler:
ED2LM: Encoder-Decoder to Language Model for Faster Document Re-ranking Inference. ACL (Findings) 2022: 3747-3758 - [c29]Xiaoyang Chen, Kai Hui, Ben He, Xianpei Han, Le Sun, Zheng Ye:
Incorporating Ranking Context for End-to-End BERT Re-ranking. ECIR (1) 2022: 111-127 - [c28]Vamsi Aribandi, Yi Tay, Tal Schuster, Jinfeng Rao, Huaixiu Steven Zheng, Sanket Vaibhav Mehta, Honglei Zhuang, Vinh Q. Tran, Dara Bahri, Jianmo Ni, Jai Prakash Gupta, Kai Hui, Sebastian Ruder, Donald Metzler:
ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning. ICLR 2022 - [c27]Yi Tay, Vinh Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Prakash Gupta, Tal Schuster, William W. Cohen, Donald Metzler:
Transformer Memory as a Differentiable Search Index. NeurIPS 2022 - [i18]Yi Tay, Vinh Q. Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Prakash Gupta, Tal Schuster, William W. Cohen, Donald Metzler:
Transformer Memory as a Differentiable Search Index. CoRR abs/2202.06991 (2022) - [i17]Kai Hui, Honglei Zhuang, Tao Chen, Zhen Qin, Jing Lu, Dara Bahri, Ji Ma, Jai Prakash Gupta, Cícero Nogueira dos Santos, Yi Tay, Don Metzler:
ED2LM: Encoder-Decoder to Language Model for Faster Document Re-ranking Inference. CoRR abs/2204.11458 (2022) - [i16]Kai Hui, Tao Chen, Zhen Qin, Honglei Zhuang, Fernando Diaz, Mike Bendersky, Don Metzler:
Retrieval Augmentation for T5 Re-ranker using External Sources. CoRR abs/2210.05145 (2022) - [i15]Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, Michael Bendersky:
RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses. CoRR abs/2210.10634 (2022) - [i14]Bernd Bohnet, Vinh Q. Tran, Pat Verga, Roee Aharoni, Daniel Andor, Livio Baldini Soares, Jacob Eisenstein, Kuzman Ganchev, Jonathan Herzig, Kai Hui, Tom Kwiatkowski, Ji Ma, Jianmo Ni, Tal Schuster, William W. Cohen, Michael Collins, Dipanjan Das, Donald Metzler, Slav Petrov, Kellie Webster:
Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models. CoRR abs/2212.08037 (2022) - [i13]Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky:
Learning List-Level Domain-Invariant Representations for Ranking. CoRR abs/2212.10764 (2022) - 2021
- [j3]Zhi Zheng, Kai Hui, Ben He, Xianpei Han, Le Sun, Andrew Yates:
Contextualized query expansion via unsupervised chunk selection for text retrieval. Inf. Process. Manag. 58(5): 102672 (2021) - [c26]Anoop R. Katti, Kai Hui, Adrià de Gispert, Hagen Fürstenau:
Question Answering using Web Lists. CIKM 2021: 3132-3136 - [c25]Xuanang Chen, Ben He, Kai Hui, Le Sun, Yingfei Sun:
Simplified TinyBERT: Knowledge Distillation for Document Retrieval. ECIR (2) 2021: 241-248 - [c24]Xuanang Chen, Ben He, Kai Hui, Yiran Wang, Le Sun, Yingfei Sun:
Contextualized Offline Relevance Weighting for Efficient and Effective Neural Retrieval. SIGIR 2021: 1617-1621 - [i12]Xiaoyang Chen, Kai Hui, Ben He, Xianpei Han, Le Sun, Zheng Ye:
Co-BERT: A Context-Aware BERT Retrieval Model Incorporating Local and Query-specific Context. CoRR abs/2104.08523 (2021) - [i11]Kai Hui, Klaus Berberich:
Transitivity, Time Consumption, and Quality of Preference Judgments in Crowdsourcing. CoRR abs/2104.08926 (2021) - [i10]Vamsi Aribandi, Yi Tay, Tal Schuster, Jinfeng Rao, Huaixiu Steven Zheng, Sanket Vaibhav Mehta, Honglei Zhuang, Vinh Q. Tran, Dara Bahri, Jianmo Ni, Jai Prakash Gupta, Kai Hui, Sebastian Ruder, Donald Metzler:
ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning. CoRR abs/2111.10952 (2021) - 2020
- [c23]Zhi Zheng, Kai Hui, Ben He, Xianpei Han, Le Sun, Andrew Yates:
BERT-QE: Contextualized Query Expansion for Document Re-ranking. EMNLP (Findings) 2020: 4718-4728 - [i9]Zhi Zheng, Kai Hui, Ben He, Xianpei Han, Le Sun, Andrew Yates:
BERT-QE: Contextualized Query Expansion for Document Re-ranking. CoRR abs/2009.07258 (2020) - [i8]Xuanang Chen, Ben He, Kai Hui, Le Sun, Yingfei Sun:
Simplified TinyBERT: Knowledge Distillation for Document Retrieval. CoRR abs/2009.07531 (2020)
2010 – 2019
- 2019
- [j2]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Overcoming low-utility facets for complex answer retrieval. Inf. Retr. J. 22(3-4): 395-418 (2019) - [c22]Sean MacAvaney, Andrew Yates, Kai Hui, Ophir Frieder:
Content-Based Weak Supervision for Ad-Hoc Re-Ranking. SIGIR 2019: 993-996 - 2018
- [j1]Yanhua Ran, Ben He, Kai Hui, Jungang Xu, Le Sun:
Neural relevance model using similarities with elite documents for effective clinical decision support. Int. J. Data Min. Bioinform. 20(2): 91-108 (2018) - [c21]Cancan Jin, Ben He, Kai Hui, Le Sun:
TDNN: A Two-stage Deep Neural Network for Prompt-independent Automated Essay Scoring. ACL (1) 2018: 1088-1097 - [c20]Canjia Li, Yingfei Sun, Ben He, Le Wang, Kai Hui, Andrew Yates, Le Sun, Jungang Xu:
NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval. EMNLP 2018: 4482-4491 - [c19]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Overcoming Low-Utility Facets for Complex Answer Retrieval. ProfS/KG4IR/Data:Search@SIGIR 2018: 46-47 - [c18]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Characterizing Question Facets for Complex Answer Retrieval. SIGIR 2018: 1205-1208 - [c17]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
Co-PACRR: A Context-Aware Neural IR Model for Ad-hoc Retrieval. WSDM 2018: 279-287 - [i7]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Characterizing Question Facets for Complex Answer Retrieval. CoRR abs/1805.00791 (2018) - [i6]Canjia Li, Yingfei Sun, Ben He, Le Wang, Kai Hui, Andrew Yates, Le Sun, Jungang Xu:
NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval. CoRR abs/1810.12936 (2018) - [i5]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Overcoming low-utility facets for complex answer retrieval. CoRR abs/1811.08772 (2018) - 2017
- [b1]Kai Hui:
Automatic methods for low-cost evaluation and position-aware models for neural information retrieval. Saarland University, Saarbrücken, Germany, 2017 - [c16]Yanhua Ran, Ben He, Kai Hui, Jungang Xu, Le Sun:
A document-based neural relevance model for effective clinical decision support. BIBM 2017: 798-804 - [c15]Kai Hui, Klaus Berberich:
Transitivity, Time Consumption, and Quality of Preference Judgments in Crowdsourcing. ECIR 2017: 239-251 - [c14]Kai Hui, Klaus Berberich:
Low-Cost Preference Judgment via Ties. ECIR 2017: 626-632 - [c13]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
PACRR: A Position-Aware Neural IR Model for Relevance Matching. EMNLP 2017: 1049-1058 - [c12]Kai Hui, Klaus Berberich, Ida Mele:
Dealing with Incomplete Judgments in Cascade Measures. ICTIR 2017: 83-90 - [c11]Kai Hui, Klaus Berberich:
Merge-Tie-Judge: Low-Cost Preference Judgments with Ties. ICTIR 2017: 277-280 - [c10]Sean MacAvaney, Andrew Yates, Kai Hui:
Contextualized PACRR for Complex Answer Retrieval. TREC 2017 - [c9]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
Position-Aware Representations for Relevance Matching in Neural Information Retrieval. WWW (Companion Volume) 2017: 799-800 - [i4]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
A Position-Aware Deep Model for Relevance Matching in Information Retrieval. CoRR abs/1704.03940 (2017) - [i3]Andrew Yates, Kai Hui:
DE-PACRR: Exploring Layers Inside the PACRR Model. CoRR abs/1706.08746 (2017) - [i2]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
RE-PACRR: A Context and Density-Aware Neural Information Retrieval Model. CoRR abs/1706.10192 (2017) - [i1]Sean MacAvaney, Kai Hui, Andrew Yates:
An Approach for Weakly-Supervised Deep Information Retrieval. CoRR abs/1707.00189 (2017) - 2016
- [c8]Kai Hui, Klaus Berberich:
Cluster Hypothesis in Low-Cost IR Evaluation with Different Document Representations. WWW (Companion Volume) 2016: 47-48 - 2015
- [c7]Kai Hui, Klaus Berberich:
Selective Labeling and Incomplete Label Mitigation for Low-Cost Evaluation. SPIRE 2015: 137-148 - 2014
- [c6]Kai Hui:
Towards Robust & Reusable Evaluation for Novelty & Diversity. PIKM@CIKM 2014: 9-17 - 2013
- [c5]Kai Hui, Bin Gao, Ben He, Tiejian Luo:
Sponsored Search Ad Selection by Keyword Structure Analysis. ECIR 2013: 230-241 - [c4]Yu Huang, Tiejian Luo, Xiang Wang, Kai Hui, Wengjie Wang, Ben He:
On Evaluating Query Performance Predictors. ICPCA/SWS 2013: 184-194 - 2011
- [c3]Kai Hui, Ben He, Tiejian Luo, Bin Wang:
Relevance weighting using within-document term statistics. CIKM 2011: 99-104 - [c2]Kai Hui, Ben He, Tiejian Luo, Bin Wang:
A Comparative Study of Pseudo Relevance Feedback for Ad-hoc Retrieval. ICTIR 2011: 318-322 - [c1]Xin Zhang, Kai Hui, Ben He, Tiejian Luo:
GUCAS at TREC 2011 Microblog Track. TREC 2011
Coauthor Index
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last updated on 2024-11-15 19:35 CET by the dblp team
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