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2020 – today
- 2023
[c54]Haitao Li
, Qingyao Ai, Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Zheng Liu, Zhao Cao:
Constructing Tree-based Index for Efficient and Effective Dense Retrieval. SIGIR 2023: 131-140- [c53]Haitao Li, Qingyao Ai, Jia Chen, Qian Dong, Yueyue Wu, Yiqun Liu, Chong Chen, Qi Tian:
SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval. SIGIR 2023: 1035-1044 - [c52]Haitian Chen, Qingyao Ai, Zhijing Wu, Zhihong Wang, Yiqun Liu, Min Zhang, Shaoping Ma, Juan Hu, Naiqiang Tan, Hua Chai:
Behavior Modeling for Point of Interest Search. SIGIR 2023: 1843-1847 - [c51]Qingyao Ai, Xuanhui Wang, Michael Bendersky:
Metric-agnostic Ranking Optimization. SIGIR 2023: 2669-2680 - [c50]Tao Yang, Zhichao Xu, Zhenduo Wang, Anh Tran, Qingyao Ai:
Marginal-Certainty-Aware Fair Ranking Algorithm. WSDM 2023: 24-32 - [c49]Dan Luo, Lixin Zou, Qingyao Ai, Zhiyu Chen, Dawei Yin, Brian D. Davison:
Model-based Unbiased Learning to Rank. WSDM 2023: 895-903 - [c48]Zhenduo Wang, Yuancheng Tu, Corby Rosset, Nick Craswell, Ming Wu, Qingyao Ai:
Zero-shot Clarifying Question Generation for Conversational Search. WWW 2023: 3288-3298 - [i57]Zhichao Xu, Hemank Lamba, Qingyao Ai, Joel R. Tetreault, Alex Jaimes:
Counterfactual Editing for Search Result Explanation. CoRR abs/2301.10389 (2023) - [i56]Ruizhe Zhang, Qingyao Ai, Yueyue Wu, Yixiao Ma, Yiqun Liu:
Diverse legal case search. CoRR abs/2301.12504 (2023) - [i55]Zhenduo Wang, Yuancheng Tu, Corby Rosset, Nick Craswell, Ming Wu, Qingyao Ai:
Zero-shot Clarifying Question Generation for Conversational Search. CoRR abs/2301.12660 (2023) - [i54]Haitao Li, Jia Chen, Weihang Su, Qingyao Ai, Yiqun Liu:
Towards Better Web Search Performance: Pre-training, Fine-tuning and Learning to Rank. CoRR abs/2303.04710 (2023) - [i53]Zhenduo Wang, Zhichao Xu, Qingyao Ai, Vivek Srikumar:
An In-depth Investigation of User Response Simulation for Conversational Search. CoRR abs/2304.07944 (2023) - [i52]Zhenduo Wang, Zhichao Xu, Qingyao Ai:
Reward-free Policy Imitation Learning for Conversational Search. CoRR abs/2304.07988 (2023) - [i51]Qingyao Ai, Xuanhui Wang, Michael Bendersky:
Metric-agnostic Ranking Optimization. CoRR abs/2304.08062 (2023) - [i50]Haitao Li, Qingyao Ai, Jia Chen, Qian Dong, Yueyue Wu, Yiqun Liu, Chong Chen, Qi Tian:
SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval. CoRR abs/2304.11370 (2023) - [i49]Haitao Li, Qingyao Ai, Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Zheng Liu, Zhao Cao:
Constructing Tree-based Index for Efficient and Effective Dense Retrieval. CoRR abs/2304.11943 (2023) - [i48]Jia Chen, Haitao Li, Weihang Su, Qingyao Ai, Yiqun Liu:
THUIR at WSDM Cup 2023 Task 1: Unbiased Learning to Rank. CoRR abs/2304.12650 (2023) - [i47]Yixiao Ma, Yueyue Wu, Weihang Su, Qingyao Ai, Yiqun Liu:
CaseEncoder: A Knowledge-enhanced Pre-trained Model for Legal Case Encoding. CoRR abs/2305.05393 (2023) - [i46]Haitao Li, Weihang Su, Changyue Wang, Yueyue Wu, Qingyao Ai, Yiqun Liu:
THUIR@COLIEE 2023: Incorporating Structural Knowledge into Pre-trained Language Models for Legal Case Retrieval. CoRR abs/2305.06812 (2023) - [i45]Haitao Li, Changyue Wang, Weihang Su, Yueyue Wu, Qingyao Ai, Yiqun Liu:
THUIR@COLIEE 2023: More Parameters and Legal Knowledge for Legal Case Entailment. CoRR abs/2305.06817 (2023) - [i44]Dan Luo, Lixin Zou, Qingyao Ai, Zhiyu Chen, Chenliang Li, Dawei Yin, Brian D. Davison:
Unconfounded Propensity Estimation for Unbiased Ranking. CoRR abs/2305.09918 (2023) - [i43]Tao Yang, Cuize Han, Chen Luo, Parth Gupta, Jeff M. Phillips, Qingyao Ai:
Mitigating Exploitation Bias in Learning to Rank with an Uncertainty-aware Empirical Bayes Approach. CoRR abs/2305.16606 (2023) - [i42]Tao Yang, Zhichao Xu, Zhenduo Wang, Qingyao Ai:
FARA: Future-aware Ranking Algorithm for Fairness Optimization. CoRR abs/2305.16637 (2023) - [i41]Qian Dong, Yiding Liu, Qingyao Ai, Haitao Li, Shuaiqiang Wang, Yiqun Liu, Dawei Yin, Shaoping Ma:
I^3 Retriever: Incorporating Implicit Interaction in Pre-trained Language Models for Passage Retrieval. CoRR abs/2306.02371 (2023) - [i40]Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu:
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community. CoRR abs/2307.09751 (2023) - [i39]Yunqiu Shao, Haitao Li, Yueyue Wu, Yiqun Liu, Qingyao Ai, Jiaxin Mao, Yixiao Ma, Shaoping Ma:
An Intent Taxonomy of Legal Case Retrieval. CoRR abs/2307.13298 (2023) - 2022
- [j8]Zhenduo Wang, Qingyao Ai:
Simulating and Modeling the Risk of Conversational Search. ACM Trans. Inf. Syst. 40(4): 85:1-85:33 (2022) - [c47]Yinqiong Cai, Jiafeng Guo, Yixing Fan, Qingyao Ai, Ruqing Zhang, Xueqi Cheng:
Hard Negatives or False Negatives: Correcting Pooling Bias in Training Neural Ranking Models. CIKM 2022: 118-127 - [c46]Tao Yang, Chen Luo, Hanqing Lu, Parth Gupta, Bing Yin, Qingyao Ai:
Can Clicks Be Both Labels and Features?: Unbiased Behavior Feature Collection and Uncertainty-aware Learning to Rank. SIGIR 2022: 6-17 - [c45]Yixiao Ma, Qingyao Ai, Yueyue Wu, Yunqiu Shao, Yiqun Liu, Min Zhang, Shaoping Ma:
Incorporating Retrieval Information into the Truncation of Ranking Lists for Better Legal Search. SIGIR 2022: 438-448 - [i38]Zhenduo Wang, Qingyao Ai:
Simulating and Modeling the Risk of Conversational Search. CoRR abs/2201.00235 (2022) - [i37]Tao Yang, Zhichao Xu, Qingyao Ai:
Effective Exposure Amortizing for Fair Top-k Recommendation. CoRR abs/2204.03046 (2022) - [i36]Zhichao Xu, Yi Han, Tao Yang, Anh Tran, Qingyao Ai:
Learning to Rank Rationales for Explainable Recommendation. CoRR abs/2206.05368 (2022) - [i35]Dan Luo, Lixin Zou, Qingyao Ai, Zhiyu Chen, Dawei Yin, Brian D. Davison:
Model-based Unbiased Learning to Rank. CoRR abs/2207.11785 (2022) - [i34]Jingtao Zhan, Qingyao Ai, Yiqun Liu, Jiaxin Mao, Xiaohui Xie, Min Zhang, Shaoping Ma:
Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrieval. CoRR abs/2208.05753 (2022) - [i33]Zhichao Xu, Anh Tran, Tao Yang, Qingyao Ai:
Reinforcement Learning to Rank with Coarse-grained Labels. CoRR abs/2208.07563 (2022) - [i32]Yinqiong Cai, Jiafeng Guo, Yixing Fan, Qingyao Ai, Ruqing Zhang, Xueqi Cheng:
Hard Negatives or False Negatives: Correcting Pooling Bias in Training Neural Ranking Models. CoRR abs/2209.05072 (2022) - [i31]Tao Yang, Zhichao Xu, Zhenduo Wang, Anh Tran, Qingyao Ai:
Marginal-Certainty-aware Fair Ranking Algorithm. CoRR abs/2212.09031 (2022) - 2021
- [j7]Qingyao Ai, Tao Yang, Huazheng Wang, Jiaxin Mao:
Unbiased Learning to Rank: Online or Offline? ACM Trans. Inf. Syst. 39(2): 21:1-21:29 (2021) - [c44]Qingyao Ai, Lakshmi Narayanan Ramasamy:
Model-agnostic vs. Model-intrinsic Interpretability for Explainable Product Search. CIKM 2021: 5-15 - [c43]Anh Tran, Tao Yang, Qingyao Ai:
ULTRA: An Unbiased Learning To Rank Algorithm Toolbox. CIKM 2021: 4613-4622 - [c42]Hansi Zeng, Zhichao Xu, Qingyao Ai:
A Zero Attentive Relevance Matching Network for Review Modeling in Recommendation System. ECIR (1) 2021: 724-739 - [c41]Qingyao Ai:
Session details: Session 1A - Ranking (1). ICTIR 2021 - [c40]Zhichao Xu, Hansi Zeng, Qingyao Ai:
Understanding the Effectiveness of Reviews in E-commerce Top-N Recommendation. ICTIR 2021: 149-155 - [c39]Keping Bi, Qingyao Ai, W. Bruce Croft:
Asking Clarifying Questions Based on Negative Feedback in Conversational Search. ICTIR 2021: 157-166 - [c38]Xiaoqiang Zhu, Kuang-chih Lee, Guorui Zhou, Biye Jiang, Zhe Wang, Ruiming Tang, Kan Ren, Qingyao Ai, Weinan Zhang:
3rd International Workshop on Deep Learning Practice for High-Dimensional Sparse Data with KDD 2021. KDD 2021: 4187-4188 - [c37]Keping Bi, Qingyao Ai, W. Bruce Croft:
Learning a Fine-Grained Review-based Transformer Model for Personalized Product Search. SIGIR 2021: 123-132 - [c36]Liang Pang, Qingyao Ai, Jun Xu:
Beyond Probability Ranking Principle: Modeling the Dependencies among Documents. SIGIR 2021: 2647-2650 - [c35]Liang Pang, Qingyao Ai, Jun Xu:
Beyond Probability Ranking Principle: Modeling the Dependencies among Documents. WSDM 2021: 1137-1140 - [c34]Tao Yang, Qingyao Ai:
Maximizing Marginal Fairness for Dynamic Learning to Rank. WWW 2021: 137-145 - [c33]Zhenduo Wang, Qingyao Ai:
Controlling the Risk of Conversational Search via Reinforcement Learning. WWW 2021: 1968-1977 - [i30]Zhenduo Wang, Qingyao Ai:
Controlling the Risk of Conversational Search via Reinforcement Learning. CoRR abs/2101.06327 (2021) - [i29]Hansi Zeng, Zhichao Xu, Qingyao Ai:
A Zero Attentive Relevance Matching Networkfor Review Modeling in Recommendation System. CoRR abs/2101.06387 (2021) - [i28]Tao Yang, Qingyao Ai:
Maximizing Marginal Fairness for Dynamic Learning to Rank. CoRR abs/2102.09670 (2021) - [i27]Qingyao Ai, Brendan O'Connor, W. Bruce Croft:
A Neural Passage Model for Ad-hoc Document Retrieval. CoRR abs/2103.09306 (2021) - [i26]Zhichao Xu, Hansi Zeng, Qingyao Ai:
Understanding the Effectiveness of Reviews in E-commerce Top-N Recommendation. CoRR abs/2106.09665 (2021) - [i25]Keping Bi, Qingyao Ai, W. Bruce Croft:
Asking Clarifying Questions Based on Negative Feedback in Conversational Search. CoRR abs/2107.05760 (2021) - [i24]Anh Tran, Tao Yang, Qingyao Ai:
ULTRA: An Unbiased Learning To Rank Algorithm Toolbox. CoRR abs/2108.05073 (2021) - [i23]Qingyao Ai, Lakshmi Narayanan Ramasamy:
Model-agnostic vs. Model-intrinsic Interpretability for Explainable Product Search. CoRR abs/2108.05317 (2021) - 2020
- [j6]Jiafeng Guo, Yixing Fan, Liang Pang, Liu Yang, Qingyao Ai, Hamed Zamani, Chen Wu, W. Bruce Croft, Xueqi Cheng:
A Deep Look into neural ranking models for information retrieval. Inf. Process. Manag. 57(6): 102067 (2020) - [j5]Qingyao Ai, Yongfeng Zhang, Keping Bi, W. Bruce Croft:
Explainable Product Search with a Dynamic Relation Embedding Model. ACM Trans. Inf. Syst. 38(1): 4:1-4:29 (2020) - [c32]Zhichao Xu, Yi Han, Yongfeng Zhang, Qingyao Ai:
E-commerce Recommendation with Weighted Expected Utility. CIKM 2020: 1695-1704 - [c31]Tao Yang, Shikai Fang, Shibo Li, Yulan Wang, Qingyao Ai:
Analysis of Multivariate Scoring Functions for Automatic Unbiased Learning to Rank. CIKM 2020: 2277-2280 - [c30]Liang Pang, Jun Xu, Qingyao Ai, Yanyan Lan, Xueqi Cheng, Jirong Wen:
SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval. SIGIR 2020: 499-508 - [c29]Keping Bi, Qingyao Ai, W. Bruce Croft:
A Transformer-based Embedding Model for Personalized Product Search. SIGIR 2020: 1521-1524 - [i22]Keping Bi, Qingyao Ai, W. Bruce Croft:
A Review-based Transformer Model for Personalized Product Search. CoRR abs/2004.09424 (2020) - [i21]Qingyao Ai, Tao Yang, Huazheng Wang, Jiaxin Mao:
Unbiased Learning to Rank: Online or Offline? CoRR abs/2004.13574 (2020) - [i20]Keping Bi, Qingyao Ai, W. Bruce Croft:
A Transformer-based Embedding Model for Personalized Product Search. CoRR abs/2005.08936 (2020) - [i19]Zhichao Xu, Yi Han, Yongfeng Zhang, Qingyao Ai:
E-commerce Recommendation with Weighted Expected Utility. CoRR abs/2008.08302 (2020) - [i18]Tao Yang, Shikai Fang, Shibo Li, Yulan Wang, Qingyao Ai:
Analysis of Multivariate Scoring Functions for Automatic Unbiased Learning to Rank. CoRR abs/2008.09061 (2020) - [i17]Zhimeng Pan, Wenzheng Tao, Qingyao Ai:
Review Regularized Neural Collaborative Filtering. CoRR abs/2008.13527 (2020) - [i16]Hansi Zeng, Qingyao Ai:
A Hierarchical Self-attentive Convolution Network for Review Modeling in Recommendation Systems. CoRR abs/2011.13436 (2020)
2010 – 2019
- 2019
- [j4]Yukun Zheng, Yiqun Liu, Zhen Fan, Cheng Luo, Qingyao Ai, Min Zhang, Shaoping Ma:
Investigating Weak Supervision in Deep Ranking. Data Inf. Manag. 3(3): 155-164 (2019) - [j3]Qingyao Ai:
Neural generative models and representation learning for information retrieval. SIGIR Forum 53(2): 97 (2019) - [c28]Keping Bi, Qingyao Ai, Yongfeng Zhang, W. Bruce Croft:
Conversational Product Search Based on Negative Feedback. CIKM 2019: 359-368 - [c27]Qingyao Ai, Daniel N. Hill, S. V. N. Vishwanathan, W. Bruce Croft:
A Zero Attention Model for Personalized Product Search. CIKM 2019: 379-388 - [c26]Xiaohui Xie, Jiaxin Mao, Yiqun Liu, Maarten de Rijke, Qingyao Ai, Yufei Huang, Min Zhang, Shaoping Ma:
Improving Web Image Search with Contextual Information. CIKM 2019: 1683-1692 - [c25]Ruey-Cheng Chen, Qingyao Ai, Gaya Jayasinghe, W. Bruce Croft:
Correcting for Recency Bias in Job Recommendation. CIKM 2019: 2185-2188 - [c24]Keping Bi, Qingyao Ai, W. Bruce Croft:
Iterative Relevance Feedback for Answer Passage Retrieval with Passage-Level Semantic Match. ECIR (1) 2019: 558-572 - [c23]Qingyao Ai, Xuanhui Wang, Sebastian Bruch, Nadav Golbandi, Michael Bendersky, Marc Najork:
Learning Groupwise Multivariate Scoring Functions Using Deep Neural Networks. ICTIR 2019: 85-92 - [c22]Yongfeng Zhang, Jiaxin Mao, Qingyao Ai:
SIGIR 2019 Tutorial on Explainable Recommendation and Search. SIGIR 2019: 1417-1418 - [c21]Yixing Fan, Qingyao Ai, Zhaochun Ren, Liangjie Hong, Dawei Yin, Jiafeng Guo:
DAPA: The WSDM 2019 Workshop on Deep Matching in Practical Applications. WSDM 2019: 844-845 - [c20]Yongfeng Zhang, Jiaxin Mao, Qingyao Ai:
WWW'19 Tutorial on Explainable Recommendation and Search. WWW (Companion Volume) 2019: 1330-1331 - [i15]Jiafeng Guo, Yixing Fan, Liang Pang, Liu Yang, Qingyao Ai, Hamed Zamani, Chen Wu, W. Bruce Croft, Xueqi Cheng:
A Deep Look into Neural Ranking Models for Information Retrieval. CoRR abs/1903.06902 (2019) - [i14]Qingyao Ai, Daniel N. Hill, S. V. N. Vishwanathan, W. Bruce Croft:
A Zero Attention Model for Personalized Product Search. CoRR abs/1908.11322 (2019) - [i13]Keping Bi, Qingyao Ai, Yongfeng Zhang, W. Bruce Croft:
Conversational Product Search Based on Negative Feedback. CoRR abs/1909.02071 (2019) - [i12]Qingyao Ai, Yongfeng Zhang, Keping Bi, W. Bruce Croft:
Explainable Product Search with a Dynamic Relation Embedding Model. CoRR abs/1909.07212 (2019) - [i11]Liang Pang, Jun Xu, Qingyao Ai, Yanyan Lan, Xueqi Cheng, Jirong Wen:
SetRank: Learning a Permutation-Invariant Ranking Model for Information Retrieval. CoRR abs/1912.05891 (2019) - 2018
- [j2]Qingyao Ai, Vahid Azizi, Xu Chen, Yongfeng Zhang:
Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation. Algorithms 11(9): 137 (2018) - [c19]Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, W. Bruce Croft:
Towards Conversational Search and Recommendation: System Ask, User Respond. CIKM 2018: 177-186 - [c18]Qingyao Ai, Jiaxin Mao, Yiqun Liu, W. Bruce Croft:
Unbiased Learning to Rank: Theory and Practice. CIKM 2018: 2305-2306 - [c17]Qingyao Ai, Brendan O'Connor, W. Bruce Croft:
A Neural Passage Model for Ad-hoc Document Retrieval. ECIR 2018: 537-543 - [c16]Qingyao Ai, Jiaxin Mao, Yiqun Liu, W. Bruce Croft:
Unbiased Learning to Rank: Theory and Practice. ICTIR 2018: 1-2 - [c15]Qingyao Ai, Keping Bi, Jiafeng Guo, W. Bruce Croft:
Learning a Deep Listwise Context Model for Ranking Refinement. SIGIR 2018: 135-144 - [c14]Qingyao Ai, Keping Bi, Cheng Luo, Jiafeng Guo, W. Bruce Croft:
Unbiased Learning to Rank with Unbiased Propensity Estimation. SIGIR 2018: 385-394 - [i10]Liu Yang, Qingyao Ai, Jiafeng Guo, W. Bruce Croft:
aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model. CoRR abs/1801.01641 (2018) - [i9]Yongfeng Zhang, Qingyao Ai, Xu Chen, Pengfei Wang:
Learning over Knowledge-Base Embeddings for Recommendation. CoRR abs/1803.06540 (2018) - [i8]Qingyao Ai, Keping Bi, Jiafeng Guo, W. Bruce Croft:
Learning a Deep Listwise Context Model for Ranking Refinement. CoRR abs/1804.05936 (2018) - [i7]Qingyao Ai, Keping Bi, Cheng Luo, Jiafeng Guo, W. Bruce Croft:
Unbiased Learning to Rank with Unbiased Propensity Estimation. CoRR abs/1804.05938 (2018) - [i6]Qingyao Ai, Vahid Azizi, Xu Chen, Yongfeng Zhang:
Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation. CoRR abs/1805.03352 (2018) - [i5]Qingyao Ai, Xuanhui Wang, Nadav Golbandi, Michael Bendersky, Marc Najork:
Learning Groupwise Scoring Functions Using Deep Neural Networks. CoRR abs/1811.04415 (2018) - [i4]Keping Bi, Qingyao Ai, W. Bruce Croft:
Revisiting Iterative Relevance Feedback for Document and Passage Retrieval. CoRR abs/1812.05731 (2018) - [i3]Keping Bi, Qingyao Ai, W. Bruce Croft:
Iterative Relevance Feedback for Answer Passage Retrieval with Passage-level Semantic Match. CoRR abs/1812.08870 (2018) - 2017
- [j1]Zeyang Liu, Jiaxin Mao, Chao Wang, Qingyao Ai, Yiqun Liu, Jian-Yun Nie:
Enhancing click models with mouse movement information. Inf. Retr. J. 20(1): 53-80 (2017) - [c13]Kanika Narang, Susan T. Dumais, Nick Craswell, Daniel J. Liebling, Qingyao Ai:
Large-Scale Analysis of Email Search and Organizational Strategies. CHIIR 2017: 215-223 - [c12]Yongfeng Zhang, Qingyao Ai, Xu Chen, W. Bruce Croft:
Joint Representation Learning for Top-N Recommendation with Heterogeneous Information Sources. CIKM 2017: 1449-1458 - [c11]Xu Chen, Yongfeng Zhang, Qingyao Ai, Hongteng Xu, Junchi Yan, Zheng Qin:
Personalized Key Frame Recommendation. SIGIR 2017: 315-324 - [c10]Qingyao Ai, Yongfeng Zhang, Keping Bi, Xu Chen, W. Bruce Croft:
Learning a Hierarchical Embedding Model for Personalized Product Search. SIGIR 2017: 645-654 - [c9]Qingyao Ai, Hamed Zamani, Stephen M. Harding, Shahrzad Naseri, James Allan, W. Bruce Croft:
UMass at TREC 2017 Common Core Track. TREC 2017 - [c8]Qingyao Ai, Susan T. Dumais, Nick Craswell, Daniel J. Liebling:
Characterizing Email Search using Large-scale Behavioral Logs and Surveys. WWW 2017: 1511-1520 - [i2]Jiafeng Guo, Yixing Fan, Qingyao Ai, W. Bruce Croft:
A Deep Relevance Matching Model for Ad-hoc Retrieval. CoRR abs/1711.08611 (2017) - 2016
- [c7]Jiafeng Guo, Yixing Fan, Qingyao Ai, W. Bruce Croft:
A Deep Relevance Matching Model for Ad-hoc Retrieval. CIKM 2016: 55-64 - [c6]Liu Yang, Qingyao Ai, Jiafeng Guo, W. Bruce Croft:
aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model. CIKM 2016: 287-296 - [c5]Jiafeng Guo, Yixing Fan, Qingyao Ai, W. Bruce Croft:
Semantic Matching by Non-Linear Word Transportation for Information Retrieval. CIKM 2016: 701-710 - [c4]Liu Yang, Qingyao Ai, Damiano Spina, Ruey-Cheng Chen, Liang Pang, W. Bruce Croft, Jiafeng Guo, Falk Scholer:
Beyond Factoid QA: Effective Methods for Non-factoid Answer Sentence Retrieval. ECIR 2016: 115-128 - [c3]Qingyao Ai, Liu Yang, Jiafeng Guo, W. Bruce Croft:
Analysis of the Paragraph Vector Model for Information Retrieval. ICTIR 2016: 133-142 - [c2]Qingyao Ai, Liu Yang, Jiafeng Guo, W. Bruce Croft:
Improving Language Estimation with the Paragraph Vector Model for Ad-hoc Retrieval. SIGIR 2016: 869-872 - [i1]Daniel Cohen, Qingyao Ai, W. Bruce Croft:
Adaptability of Neural Networks on Varying Granularity IR Tasks. CoRR abs/1606.07565 (2016) - 2015
- [c1]Chia-Jung Lee, Qingyao Ai, W. Bruce Croft, Daniel Sheldon:
An Optimization Framework for Merging Multiple Result Lists. CIKM 2015: 303-312
Coauthor Index