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Kai Hui
Kai Hui
Software Engineer, Google Research
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
Pacrr: A position-aware neural ir model for relevance matching
K Hui, A Yates, K Berberich, G de Melo
Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017
1942017
Ext5: Towards extreme multi-task scaling for transfer learning
V Aribandi, Y Tay, T Schuster, J Rao, HS Zheng, SV Mehta, H Zhuang, ...
arXiv preprint arXiv:2111.10952, 2021
1572021
Co-PACRR: A context-aware neural IR model for ad-hoc retrieval
K Hui, A Yates, K Berberich, G De Melo
Proceedings of the eleventh ACM international conference on web search and …, 2018
1342018
Transformer memory as a differentiable search index
Y Tay, V Tran, M Dehghani, J Ni, D Bahri, H Mehta, Z Qin, K Hui, Z Zhao, ...
Advances in Neural Information Processing Systems 35, 21831-21843, 2022
1302022
TDNN: a two-stage deep neural network for prompt-independent automated essay scoring
C Jin, B He, K Hui, L Sun
Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018
1002018
BERT-QE: contextualized query expansion for document re-ranking
Z Zheng, K Hui, B He, X Han, L Sun, A Yates
arXiv preprint arXiv:2009.07258, 2020
89*2020
NPRF: A neural pseudo relevance feedback framework for ad-hoc information retrieval
C Li, Y Sun, B He, L Wang, K Hui, A Yates, L Sun, J Xu
Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018
692018
Attributed question answering: Evaluation and modeling for attributed large language models
B Bohnet, VQ Tran, P Verga, R Aharoni, D Andor, LB Soares, M Ciaramita, ...
arXiv preprint arXiv:2212.08037, 2022
552022
Large language models are effective text rankers with pairwise ranking prompting
Z Qin, R Jagerman, K Hui, H Zhuang, J Wu, J Shen, T Liu, J Liu, D Metzler, ...
arXiv preprint arXiv:2306.17563, 2023
532023
Content-Based Weak Supervision for Ad-Hoc Re-Ranking
S MacAvaney, A Yates, K Hui, O Frieder
Proceedings of the 42nd International ACM SIGIR Conference on Research and …, 2019
452019
Rankt5: Fine-tuning t5 for text ranking with ranking losses
H Zhuang, Z Qin, R Jagerman, K Hui, J Ma, J Lu, J Ni, X Wang, ...
Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023
392023
Simplified tinybert: Knowledge distillation for document retrieval
X Chen, B He, K Hui, L Sun, Y Sun
Advances in Information Retrieval: 43rd European Conference on IR Research …, 2021
292021
How Does Generative Retrieval Scale to Millions of Passages?
R Pradeep, K Hui, J Gupta, AD Lelkes, H Zhuang, J Lin, D Metzler, ...
arXiv preprint arXiv:2305.11841, 2023
192023
An approach for weakly-supervised deep information retrieval
S MacAvaney, K Hui, A Yates
The Second SIGIR Workshop on Neural Information Retrieval (Neu-IR'17), 2017
192017
Incorporating ranking context for end-to-end BERT re-ranking
X Chen, K Hui, B He, X Han, L Sun, Z Ye
European Conference on Information Retrieval, 111-127, 2022
15*2022
Transitivity, time consumption, and quality of preference judgments in crowdsourcing
K Hui, K Berberich
Advances in Information Retrieval: 39th European Conference on IR Research …, 2017
152017
ED2LM: Encoder-Decoder to Language Model for Faster Document Re-ranking Inference
K Hui, H Zhuang, T Chen, Z Qin, J Lu, D Bahri, J Ma, J Gupta, ...
ACL 2022: Findings, 2022
142022
Characterizing question facets for complex answer retrieval
S MacAvaney, A Yates, A Cohan, L Soldaini, K Hui, N Goharian, O Frieder
The 41st International ACM SIGIR Conference on Research & Development in …, 2018
142018
A comparative study of pseudo relevance feedback for ad-hoc retrieval
K Hui, B He, T Luo, B Wang
Advances in Information Retrieval Theory: Third International Conference …, 2011
142011
Beyond yes and no: Improving zero-shot llm rankers via scoring fine-grained relevance labels
H Zhuang, Z Qin, K Hui, J Wu, L Yan, X Wang, M Berdersky
arXiv preprint arXiv:2310.14122, 2023
122023
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