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This blog summarizes the latest research development of Retrieval papers published in KDD2023 conferences. This year there are total 8 papers related to Retrieval in KDD2023. Most of the authors' affiliations are top research institutes (Google Research, DeepMind, Meta FAIR) and universities (Stanford, Berkeley, MIT, CMU and others).
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- 1.CFGL-LCR: A Counterfactual Graph Learning framework for Legal Case Retrieval
- 2.Dense Representation Learning and Retrieval for Tabular Data Prediction
- 3.Learning Balanced Tree Indexes for Large-Scale Vector Retrieval
- 4.Binary Embedding-Based Retrieval at Tencent
- 5.MUSER: A Multi-Step Evidence Retrieval Enhancement Framework for Fake News Detection
- 6.An Empirical Study of Selection Bias in Pinterest Ads Retrieval
- 7.UnifieR: A Unified Retriever for Large-Scale Retrieval
- 8.Revisiting Neural Retrieval on Accelerators
Paper List
1.CFGL-LCR: A Counterfactual Graph Learning framework for Legal Case Retrieval
Kun Zhang (Institute of Computing Technology, Chinese Academy of Sciences), Chong Chen (Huawei Cloud BU.), Yuanzhuo Wang (Institute of Computing Technology, Chinese Academy of Sciences), Qi Tian (Huawei Cloud BU.), Long Bai (Institute of Computing Technology, Chinese Academy of Sciences)
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2.Dense Representation Learning and Retrieval for Tabular Data Prediction
Lei Zheng (Shanghai Jiao Tong University), Ning Li (Shanghai Jiao Tong University), Xianyu Chen (Shanghai Jiao Tong University), Quan Gan (Shanghai Jiao Tong University), Weinan Zhang (Shanghai Jiao Tong University)
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3.Learning Balanced Tree Indexes for Large-Scale Vector Retrieval
Wuchao Li (University of Science and Technology of China), Chao Feng (University of Science and Technology of China), Defu Lian (University of Science and Technology of China), Yuxin Xie (Guangdong OPPO Mobile Telecommunications Corp., Ltd), Haifeng Liu (Guangdong OPPO Mobile Telecommunications Corp., Ltd), Yong Ge (University of Arizona), Enhong Chen (University of Science and Technology of China)
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4.Binary Embedding-Based Retrieval at Tencent
Yukang Gan (Tencent), Yixiao Ge (Tencent), Chang Zhou (Tencent), Shupeng Su (Tencent), Zhouchuan Xu (Tencent), Xuyuan Xu (Tencent), Quanchao Hui (Tencent), Xiang Chen (Tencent), Yexin Wang (Tencent), Ying Shan (Tencent)
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5.MUSER: A Multi-Step Evidence Retrieval Enhancement Framework for Fake News Detection
Hao Liao (Shenzhen University), Jiahao Peng (Shenzhen University), Zhanyi Huang (Shenzhen University), Wei Zhang (Shenzhen University), Guanghua Li (Shenzhen University), Kai Shu (Illinois Institute of Technology), Xing Xie (Microsoft Research Asia)
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6.An Empirical Study of Selection Bias in Pinterest Ads Retrieval
Yuan Wang (Santa Clara University), Peifeng Yin (Pinterest), Zhiqiang Tao Tao (Rochester Institute of Technology), Hari Venkatesan (Pinterest), Jin Lai (Pinterest), Yi Fang (Santa Clara University), PJ XIAO (Pinterest)
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7.UnifieR: A Unified Retriever for Large-Scale Retrieval
Tao Shen (University of Technology Sydney), Xiubo Geng (Microsoft), Chongyang Tao (Microsoft), Can Xu (Microsoft), Guodong Long (University of Technology Sydney), Kai Zhang (The Ohio State University), Daxin Jiang (Microsoft)
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8.Revisiting Neural Retrieval on Accelerators
Jiaqi Zhai (Meta Platforms, Inc.), Zhaojie Gong (Meta Platforms, Inc.), Yueming Wang (Meta Platforms, Inc.), Xiao Sun (Meta Platforms, Inc.), Zheng Yan (Meta Platforms, Inc.), Fu Li (Meta Platforms, Inc.), Xing Liu (Meta Platforms, Inc.)
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