SIGIR

Set2setRank: Collaborative Set to Set Ranking for Implicit Feedback based Recommendation

Lei Chen, Le Wu, Kun Zhang, Richang Hong, Meng Wang

Comments The paper is accepted by SIGIR 2021

Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling

Sebastian Hofstätter, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin, Allan Hanbury

Comments Accepted at SIGIR 2021 (Full Paper track)

Towards an Online Empathetic Chatbot with Emotion Causes

Yanran Li, Ke Li, Hongke Ning, xiaoqiang Xia, Yalong Guo, Chen Wei, Jianwei Cui, Bin Wang

Comments SIGIR 2021

Predicting Links on Wikipedia with Anchor Text Information

Robin Brochier, Frédéric Béchet

Comments ACM SIGIR Conference on Research and Development in Information Retrieval, Jul 2021, New York, France

Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue

Wenjie Wang, Fuli Feng, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

Comments Accepted by SIGIR 2021

Journal ref Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021)

Answering Any-hop Open-domain Questions with Iterative Document Reranking

Ping Nie, Yuyu Zhang, Arun Ramamurthy, Le Song

Comments Accepted by SIGIR 2021

Self-Supervised Contrastive Learning for Code Retrieval and Summarization via Semantic-Preserving Transformations

Nghi D. Q. Bui, Yijun Yu, Lingxiao Jiang

Comments Accepted at SIGIR 2021

Context-Aware Learning to Rank with Self-Attention

Przemysław Pobrotyn, Tomasz Bartczak, Mikołaj Synowiec, Radosław Białobrzeski, Jarosław Bojar

Comments 8 pages, published at SIGIR eCom'20

A General Method For Automatic Discovery of Powerful Interactions In Click-Through Rate Prediction

Ze Meng, Jinnian Zhang, Yumeng Li, Jiancheng Li, Tanchao Zhu, Lifeng Sun

Comments Accepted by ACM SIGIR 2021

Training Mixed-Objective Pointing Decoders for Block-Level Optimization in Search Recommendation

Harsh Kohli

Comments 4 pages. Accepted at the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval

De-Biased Modelling of Search Click Behavior with Reinforcement Learning

Jianghong Zhou, Sayyed M. Zahiri, Simon Hughes, Khalifeh Al Jadda, Surya Kallumadi, Eugene Agichtein

Comments SIGIR 2021 Short Paper

Partner Matters! An Empirical Study on Fusing Personas for Personalized Response Selection in Retrieval-Based Chatbots

Jia-Chen Gu, Hui Liu, Zhen-Hua Ling, Quan Liu, Zhigang Chen, Xiaodan Zhu

Comments Accepted by SIGIR 2021

Intra-Document Cascading: Learning to Select Passages for Neural Document Ranking

Sebastian Hofstätter, Bhaskar Mitra, Hamed Zamani, Nick Craswell, Allan Hanbury

Comments Accepted at SIGIR 2021 (Full Paper Track)

Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning

Yang Deng, Yaliang Li, Fei Sun, Bolin Ding, Wai Lam

Comments Accepted by SIGIR 2021

POINTREC: A Test Collection for Narrative-driven Point of Interest Recommendation

Jafar Afzali, Aleksander Mark Drzewiecki, Krisztian Balog

Comments Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '21), 2021

On Interpretation and Measurement of Soft Attributes for Recommendation

Krisztian Balog, Filip Radlinski, Alexandros Karatzoglou

Comments Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '21), 2021

Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction

Wentao Ouyang, Xiuwu Zhang, Shukui Ren, Li Li, Kun Zhang, Jinmei Luo, Zhaojie Liu, Yanlong Du

Comments SIGIR 2021

Few-Shot Conversational Dense Retrieval

Shi Yu, Zhenghao Liu, Chenyan Xiong, Tao Feng, Zhiyuan Liu

Comments Accepted by SIGIR 2021

Wizard of Search Engine: Access to Information Through Conversations with Search Engines

Pengjie Ren, Zhongkun Liu, Xiaomeng Song, Hongtao Tian, Zhumin Chen, Zhaochun Ren, Maarten de Rijke

Comments Published in SIGIR 2021

Explicit Semantic Cross Feature Learning via Pre-trained Graph Neural Networks for CTR Prediction

Feng Li, Bencheng Yan, Qingqing Long, Pengjie Wang, Wei Lin, Jian Xu, Bo Zheng

Comments SIGIR 2021, 5 pages; The first two authors contributed equally to this work; Pengjie Wang gave a lot of guidance in this work

Bootstrapping User and Item Representations for One-Class Collaborative Filtering

Dongha Lee, SeongKu Kang, Hyunjun Ju, Chanyoung Park, Hwanjo Yu

Comments SIGIR 2021. 9 pages + references (1 page). 6 figures

Video Corpus Moment Retrieval with Contrastive Learning

Hao Zhang, Aixin Sun, Wei Jing, Guoshun Nan, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh

Comments 11 pages, 7 figures and 6 tables. Accepted by SIGIR 2021

Causal Intervention for Leveraging Popularity Bias in Recommendation

Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling, Yongdong Zhang

Comments Appear in SIGIR 2021

Looking at CTR Prediction Again: Is Attention All You Need?

Yuan Cheng, Yanbo Xue

Comments 9 pages, 2 figures, 4 tables, SIGIR'21

Counterfactual Explanations for Neural Recommenders

Khanh Hiep Tran, Azin Ghazimatin, Rishiraj Saha Roy

Comments SIGIR 2021 Short Paper, 5 pages

Backretrieval: An Image-Pivoted Evaluation Metric for Cross-Lingual Text Representations Without Parallel Corpora

Mikhail Fain, Niall Twomey, Danushka Bollegala

Comments SIGIR 2021

Learning to Ask Appropriate Questions in Conversational Recommendation

Xuhui Ren, Hongzhi Yin, Tong Chen, Hao Wang, Zi Huang, Kai Zheng

Comments to be published in SIGIR'2021

Scalable Personalised Item Ranking through Parametric Density Estimation

Riku Togashi, Masahiro Kato, Mayu Otani, Tetsuya Sakai, Shin'ichi Satoh

Comments Accepted by SIGIR'21

Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models

Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, Carsten Eickhoff

Comments ACM SIGIR preprint

Societal Biases in Retrieved Contents: Measurement Framework and Adversarial Mitigation for BERT Rankers

Navid Rekabsaz, Simone Kopeinik, Markus Schedl

Comments Accepted at SIGIR 2021