Must-read Papers on Neural Information Retrieval
- A Deep Look into Neural Ranking Models for Information Retrieval. Jiafeng Guo, Yixing Fan, Liang Pang, Liu Yang, Qingyao Ai, Hamed Zamani, Chen Wu, W. Bruce Croft, Xueqi Cheng. paper
- Learning Deep Structured Semantic Models for Web Search using Clickthrough Data. Po-Sen Huang, Xiaodong He, Jianfeng Gao, Li Deng, Alex Acero, Larry Heck. CIKM 2013. paper
- Convolutional Neural Network Architectures for Matching Natural Language Sentences. Baotian Hu, Zhengdong Lu, Hang Li, Qingcai Chen. NeurIPS 2014. paper
- Learning Semantic Representations Using Convolutional Neural Networks for Web Search. Yelong Shen, Xiaodong He, Jianfeng Gao, Li Deng, Grégoire Mesnil. WWW 2014. paper
- A Deep Relevance Matching Model for Ad-hoc Retrieval. Jiafeng Guo, Yixing Fan, Qingyao Ai, W. Bruce Croft. CIKM 2016. paper
- aNMM: Ranking Short Answer Texts with Attention-Based Neural Matching Model. Liu Yang, Qingyao Ai, Jiafeng Guo, W. Bruce Croft. CIKM 2016. paper
- Text Matching as Image Recognition. Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, Shengxian Wan, Xueqi Cheng. AAAI 2016. paper
- Machine Comprehension Using Match-LSTM and Answer Pointer. Shuohang Wang, Jing Jiang. ICLR 2017. paper
- Learning to Match Using Local and Distributed Representations of Text for Web Search. Bhaskar Mitra, Fernando Diaz, Nick Craswell. WWW 2017. paper
- End-to-End Neural Ad-hoc Ranking with Kernel Pooling. Chenyan Xiong, Zhuyun Dai, Jamie Callan, Zhiyuan Liu, Russell Power. SIGIR 2017. paper
- Convolutional Neural Networks for Soft-Matching N-Grams in Ad-hoc Search. Zhuyun Dai, Chenyan Xiong, Jamie Callan, Zhiyuan Liu. WSDM 2018. paper
- Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking. Sebastian Hofstätter, Markus Zlabinger, Allan Hanbury. ECAI 2020. paper
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova. NAACL-HLT 2019. paper
- Understanding the Behaviors of BERT in Ranking. Yifan Qiao, Chenyan Xiong, Zhenghao Liu, Zhiyuan Liu. arxiv 2019. paper
- SciBERT: A Pretrained Language Model for Scientific Text。 Iz Beltagy, Kyle Lo, Arman Cohan. EMNLP 2019. paper
- Deeper Text Understanding for IR with Contextual Neural Language Modeling. Zhuyun Dai, Jamie Callan. SIGIR 2019. paper
- RoBERTa: A Robustly Optimized BERT Pretraining Approach. Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, Veselin Stoyanov. arxiv 2019. paper
- ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators. Kevin Clark, Minh-Thang Luong, Quoc V. Le, Christopher D. Manning. ICLR 2020. paper
- Complementing Lexical Retrieval with Semantic Residual Embedding. Luyu Gao, Zhuyun Dai, Zhen Fan, Jamie Callan. arxiv 2020. paper
- Dense Passage Retrieval for Open-Domain Question Answering. Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, Wen-tau Yih. arxiv 2020. paper
- Latent Retrieval for Weakly Supervised Open Domain Question Answering. Kenton Lee, Ming-Wei Chang, Kristina Toutanova ACL 2019. paper
- Pre-training Tasks for Embedding-based Large-scale Retrieval. Wei-Cheng Chang, Felix X. Yu, Yin-Wen Chang, Yiming Yang, Sanjiv Kumar. arxiv 2020. paper
- Sparse, Dense, and Attentional Representations for Text Retrieval. Yi Luan, Jacob Eisenstein, Kristina Toutanova, Michael Collins. arxiv 2020. paper
- REALM: Retrieval-Augmented Language Model Pre-Training. Yi Luan, Jacob Eisenstein, Kristina Toutanova, Michael Collins. arxiv 2020. paper
- Explicit Semantic Ranking for Academic Search via Knowledge Graph Embedding. Chenyan Xiong, Russell Power, Jamie Callan. WWW 2017. paper
- Word-entity duet representations for document ranking. Chenyan Xiong, Jamie Callan, Tie-Yan Liu. SIGIR 2017. paper
- JointSem: Combining Query Entity Linking and Entity based Document Ranking. Chenyan Xiong, Zhengzhong Liu, Jamie Callan, Eduard Hovy. CIKM 2017. paper
- Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling. Chenyan Xiong, Zhengzhong Liu, Jamie Callan, Tie-Yan Liu. SIGIR 2018. paper
- Entity-Duet Neural Ranking: Understanding the Role of Knowledge Graph Semantics in Neural Information Retrieval. Zhenghao Liu, Chenyan Xiong, Maosong Sun, Zhiyuan Liu. ACL 2018. paper
- Meta-Learning in Neural Networks: A Survey. Timothy Hospedales, Antreas Antoniou, Paul Micaelli, Amos Storkey. arXiv 2020. paper
- Content-Based Weak Supervision for Ad-Hoc Re-Ranking. Sean MacAvaney, Andrew Yates, Kai Hui, Ophir Frieder. SIGIR 2019. paper
- Critically Examining the "Neural Hype": Weak Baselines and the Additivity of Effectiveness Gains from Neural Ranking Models. Wei Yang, Kuang Lu, Peilin Yang, Jimmy Lin. SIGIR 2019. paper
- Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise. Dan Hendrycks, Mantas Mazeika, Duncan Wilson, Kevin Gimpel. NeurIPS 2018. paper
- Learning to Reweight Examples for Robust Deep Learning. Mengye Ren, Wenyuan Zeng, Bin Yang, Raquel Urtasun. ICML 2018. paper
- On the Theory of Weak Supervision for Information Retrieval. Hamed Zamani, W. Bruce Croft. CTIR 2018. paper
- Co-teaching: Robust training of deep neural networks with extremely noisy labels. Bo Han, Quanming Yao, Xingrui Yu, Gang Niu, Miao Xu, Weihua Hu, Ivor Tsang, Masashi Sugiyama. NeurIPS 2018. paper
- Neural Ranking Models with Weak Supervision. Mostafa Dehghani, Hamed Zamani, Aliaksei Severyn, JaapKamps, W.Bruce. SIGIR 2017. paper
- Learning to Learn from Weak Supervision by Full Supervision. Mostafa Dehghani, Aliaksei Severyn, Sascha Rothe, JaapKamps. NeurIPS 2017. paper
- Training Deep Ranking Model with Weak Relevance Labels. ChengLuo, YukunZheng, JiaxinMao, YiqunLiu, MinZhang, ShaopingMa. ADC 2017. paper
- Selective Weak Supervision for Neural Information Retrieval. Kaitao Zhang, Chenyan Xiong, Zhenghao Liu, Zhiyuan Liu. WWW 2020. paper