Michael Bendersky
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
107
Venues
13
Active years
2008–2026
Best venue rank
A*
Where they publish
Papers
107 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | WWW | Pathways of Thoughts: Multi-Directional Thinking for Long-form Personalized Question Answering. | Alireza Salemi, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Zhuowan Li, Spurthi Amba Hombaiah, Weize Kong, Tao Chen, Hamed Zamani, Michael Bendersky |
| 2026 | SIGIR | Can QPP Choose the Right Query variant? Evaluating Query Variant Selection for RAG Pipelines. | Negar Arabzadeh, Andrew Drozdov, Michael Bendersky, Matei Zaharia |
| 2025 | ICLR | Inference Scaling for Long-Context Retrieval Augmented Generation. | Zhenrui Yue, Honglei Zhuang, Aijun Bai, Kai Hui, Rolf Jagerman, Hansi Zeng, Zhen Qin, Dong Wang, Xuanhui Wang, Michael Bendersky |
| 2024 | ACL | Bridging the Preference Gap between Retrievers and LLMs. | Zixuan Ke, Weize Kong, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky |
| 2024 | ACL | PRewrite: Prompt Rewriting with Reinforcement Learning. | Weize Kong, Spurthi Amba Hombaiah, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky |
| 2024 | ACL | LaMP: When Large Language Models Meet Personalization. | Alireza Salemi, Sheshera Mysore, Michael Bendersky, Hamed Zamani |
| 2024 | ACL | Predicting Text Preference Via Structured Comparative Reasoning. | Jing Nathan Yan, Tianqi Liu, Justin T. Chiu, Jiaming Shen, Zhen Qin, Yue Yu, Charumathi Lakshmanan, Yair Kurzion, Alexander M. Rush, Jialu Liu, Michael Bendersky |
| 2024 | ACL | Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning. | Yue Yu, Jiaming Shen, Tianqi Liu, Zhen Qin, Jing Nathan Yan, Jialu Liu, Chao Zhang, Michael Bendersky |
| 2024 | ACL | PLaD: Preference-based Large Language Model Distillation with Pseudo-Preference Pairs. | Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Haorui Wang, Zhen Qin, Feng Han, Jialu Liu, Simon Baumgartner, Michael Bendersky, Chao Zhang |
| 2024 | EMNLP | Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach. | Zhuowan Li, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky |
| 2024 | EMNLP | Multilingual Fine-Grained News Headline Hallucination Detection. | Jiaming Shen, Tianqi Liu, Jialu Liu, Zhen Qin, Jay Pavagadhi, Simon Baumgartner, Michael Bendersky |
| 2024 | EMNLP | Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing. | Le Yan, Zhen Qin, Honglei Zhuang, Rolf Jagerman, Xuanhui Wang, Michael Bendersky, Harrie Oosterhuis |
| 2024 | ICML | Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. | Lu Yin, You Wu, Zhenyu Zhang, Cheng-Yu Hsieh, Yaqing Wang, Yiling Jia, Gen Li, Ajay Kumar Jaiswal, Mykola Pechenizkiy, Yi Liang, Michael Bendersky, Zhangyang Wang, Shiwei Liu |
| 2024 | KDD | Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I. | Harrie Oosterhuis, Rolf Jagerman, Zhen Qin, Xuanhui Wang, Michael Bendersky |
| 2024 | KDD | Knowledge Distillation with Perturbed Loss: From a Vanilla Teacher to a Proxy Teacher. | Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Jialu Liu, Michael Bendersky, Marc Najork, Chao Zhang |
| 2024 | NAACL | It's All Relative! - A Synthetic Query Generation Approach for Improving Zero-Shot Relevance Prediction. | Aditi Chaudhary, Karthik Raman, Michael Bendersky |
| 2024 | NAACL | Take One Step at a Time to Know Incremental Utility of Demonstration: An Analysis on Reranking for Few-Shot In-Context Learning. | Kazuma Hashimoto, Karthik Raman, Michael Bendersky |
| 2024 | NAACL | Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting. | Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Le Yan, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, Michael Bendersky |
| 2024 | NAACL | Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels. | Honglei Zhuang, Zhen Qin, Kai Hui, Junru Wu, Le Yan, Xuanhui Wang, Michael Bendersky |
| 2024 | WWW | Learning to Rewrite Prompts for Personalized Text Generation. | Cheng Li, Mingyang Zhang, Qiaozhu Mei, Weize Kong, Michael Bendersky |
| 2024 | SIGIR | Can Query Expansion Improve Generalization of Strong Cross-Encoder Rankers? | Minghan Li, Honglei Zhuang, Kai Hui, Zhen Qin, Jimmy Lin, Rolf Jagerman, Xuanhui Wang, Michael Bendersky |
| 2024 | SIGIR | The Second Workshop on Large Language Models for Individuals, Groups, and Society. | Michael Bendersky, Cheng Li, Qiaozhu Mei, Vanessa Murdock, Jie Tang, Hongning Wang, Hamed Zamani, Mingyang Zhang, Xingjian Zhang |
| 2024 | SIGIR | Stochastic RAG: End-to-End Retrieval-Augmented Generation through Expected Utility Maximization. | Hamed Zamani, Michael Bendersky |
| 2024 | WSDM | WSDM 2024 Workshop on Large Language Models for Individuals, Groups, and Society. | Michael Bendersky, Cheng Li, Qiaozhu Mei, Vanessa Murdock, Jie Tang, Hongning Wang, Hamed Zamani, Mingyang Zhang |
| 2023 | CIKM | Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance. | Aijun Bai, Rolf Jagerman, Zhen Qin, Le Yan, Pratyush Kar, Bing-Rong Lin, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2023 | CIKM | Learning Sparse Lexical Representations Over Specified Vocabularies for Retrieval. | Jeffrey M. Dudek, Weize Kong, Cheng Li, Mingyang Zhang, Michael Bendersky |
| 2023 | EMNLP | Creator Context for Tweet Recommendation. | Spurthi Amba Hombaiah, Tao Chen, Mingyang Zhang, Michael Bendersky, Marc Najork, Matt Colen, Sergey Levi, Vladimir Ofitserov, Tanvir Amin |
| 2023 | KDD | SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. | Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky |
| 2023 | KDD | End-to-End Query Term Weighting. | Karan Samel, Cheng Li, Weize Kong, Tao Chen, Mingyang Zhang, Shaleen Kumar Gupta, Swaraj Khadanga, Wensong Xu, Xingyu Wang, Kashyap Kolipaka, Michael Bendersky, Marc Najork |
| 2023 | KDD | Towards Disentangling Relevance and Bias in Unbiased Learning to Rank. | Yunan Zhang, Le Yan, Zhen Qin, Honglei Zhuang, Jiaming Shen, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2023 | WWW | Job Type Extraction for Service Businesses. | Cheng Li, Yaping Qi, Hayk Zakaryan, Mingyang Zhang, Michael Bendersky, Yonghua Wu, Marc Najork |
| 2023 | WWW | What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis. | Xiang Deng, Vasilisa Bashlovkina, Feng Han, Simon Baumgartner, Michael Bendersky |
| 2023 | WWW | LLMs to the Moon? Reddit Market Sentiment Analysis with Large Language Models. | Xiang Deng, Vasilisa Bashlovkina, Feng Han, Simon Baumgartner, Michael Bendersky |
| 2023 | SIGIR | Metric-agnostic Ranking Optimization. | Qingyao Ai, Xuanhui Wang, Michael Bendersky |
| 2023 | SIGIR | SIGIR 2023 Workshop on Retrieval Enhanced Machine Learning (REML @ SIGIR 2023). | Michael Bendersky, Danqi Chen, Fernando Diaz, Hamed Zamani |
| 2023 | SIGIR | SparseEmbed: Learning Sparse Lexical Representations with Contextual Embeddings for Retrieval. | Weize Kong, Jeffrey M. Dudek, Cheng Li, Mingyang Zhang, Michael Bendersky |
| 2023 | SIGIR | Multivariate Representation Learning for Information Retrieval. | Hamed Zamani, Michael Bendersky |
| 2023 | SIGIR | RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses. | Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, Michael Bendersky |
| 2022 | ECIR | Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models. | Tao Chen, Mingyang Zhang, Jing Lu, Michael Bendersky, Marc Najork |
| 2022 | EMNLP | QUILL: Query Intent with Large Language Models using Retrieval Augmentation and Multi-stage Distillation. | Krishna Srinivasan, Karthik Raman, Anupam Samanta, Lingrui Liao, Luca Bertelli, Michael Bendersky |
| 2022 | ICTIR | Stochastic Retrieval-Conditioned Reranking. | Hamed Zamani, Michael Bendersky, Donald Metzler, Honglei Zhuang, Xuanhui Wang |
| 2022 | KDD | Rax: Composable Learning-to-Rank Using JAX. | Rolf Jagerman, Xuanhui Wang, Honglei Zhuang, Zhen Qin, Michael Bendersky, Marc Najork |
| 2022 | KDD | Multi-Aspect Dense Retrieval. | Weize Kong, Swaraj Khadanga, Cheng Li, Shaleen Kumar Gupta, Mingyang Zhang, Wensong Xu, Michael Bendersky |
| 2022 | KDD | Scale Calibration of Deep Ranking Models. | Le Yan, Zhen Qin, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2022 | SIGIR | On Optimizing Top-K Metrics for Neural Ranking Models. | Rolf Jagerman, Zhen Qin, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2022 | SIGIR | Revisiting Two-tower Models for Unbiased Learning to Rank. | Le Yan, Zhen Qin, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2022 | SIGIR | Retrieval-Enhanced Machine Learning. | Hamed Zamani, Fernando Diaz, Mostafa Dehghani, Donald Metzler, Michael Bendersky |
| 2022 | WSDM | Search and Discovery in Personal Email Collections. | Michael Bendersky, Xuanhui Wang, Marc Najork, Donald Metzler |
| 2021 | CIKM | Natural Language Understanding with Privacy-Preserving BERT. | Chen Qu, Weize Kong, Liu Yang, Mingyang Zhang, Michael Bendersky, Marc Najork |
| 2021 | ICLR | Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees? | Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2021 | ICTIR | Ensemble Distillation for BERT-Based Ranking Models. | Honglei Zhuang, Zhen Qin, Shuguang Han, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2021 | KDD | Bootstrapping Recommendations at Chrome Web Store. | Zhen Qin, Honglei Zhuang, Rolf Jagerman, Xinyu Qian, Po Hu, Dan Chary Chen, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2021 | KDD | Dynamic Language Models for Continuously Evolving Content. | Spurthi Amba Hombaiah, Tao Chen, Mingyang Zhang, Michael Bendersky, Marc Najork |
| 2021 | WWW | Diversification-Aware Learning to Rank using Distributed Representation. | Le Yan, Zhen Qin, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky |
| 2021 | WWW | Cross-Positional Attention for Debiasing Clicks. | Honglei Zhuang, Zhen Qin, Xuanhui Wang, Michael Bendersky, Xinyu Qian, Po Hu, Dan Chary Chen |
| 2021 | SIGIR | WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning. | Krishna Srinivasan, Karthik Raman, Jiecao Chen, Michael Bendersky, Marc Najork |
| 2021 | WSDM | Improving Cloud Storage Search with User Activity. | Rolf Jagerman, Weize Kong, Rama Kumar Pasumarthi, Zhen Qin, Michael Bendersky, Marc Najork |
| 2021 | WSDM | Interpretable Ranking with Generalized Additive Models. | Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Alexander Grushetsky, Yonghui Wu, Petr Mitrichev, Ethan Sterling, Nathan Bell, Walker Ravina, Hai Qian |
| 2020 | CIKM | Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Long-Form Document Matching. | Liu Yang, Mingyang Zhang, Cheng Li, Michael Bendersky, Marc Najork |
| 2020 | EMNLP | DiPair: Fast and Accurate Distillation for Trillion-ScaleText Matching and Pair Modeling. | Jiecao Chen, Liu Yang, Karthik Raman, Michael Bendersky, Jung-Jung Yeh, Yun Zhou, Marc Najork, Danyang Cai, Ehsan Emadzadeh |
| 2020 | ICTIR | Permutation Equivariant Document Interaction Network for Neural Learning to Rank. | Rama Kumar Pasumarthi, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2020 | KDD | Learning to Cluster Documents into Workspaces Using Large Scale Activity Logs. | Weize Kong, Michael Bendersky, Marc Najork, Brandon Vargo, Mike Colagrosso |
| 2020 | WWW | Adversarial Bandits Policy for Crawling Commercial Web Content. | Shuguang Han, Michael Bendersky, Przemek Gajda, Sergey Novikov, Marc Najork, Bernhard Brodowsky, Alexandrin Popescul |
| 2020 | WWW | Matching Cross Network for Learning to Rank in Personal Search. | Zhen Qin, Zhongliang Li, Michael Bendersky, Donald Metzler |
| 2020 | SIGIR | Feature Transformation for Neural Ranking Models. | Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2020 | WSDM | A Stochastic Treatment of Learning to Rank Scoring Functions. | Sebastian Bruch, Shuguang Han, Michael Bendersky, Marc Najork |
| 2019 | ICTIR | Learning Groupwise Multivariate Scoring Functions Using Deep Neural Networks. | Qingyao Ai, Xuanhui Wang, Sebastian Bruch, Nadav Golbandi, Michael Bendersky, Marc Najork |
| 2019 | ICTIR | An Analysis of the Softmax Cross Entropy Loss for Learning-to-Rank with Binary Relevance. | Sebastian Bruch, Xuanhui Wang, Michael Bendersky, Marc Najork |
| 2019 | ICTIR | Neural Learning to Rank using TensorFlow Ranking: A Hands-on Tutorial. | Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang |
| 2019 | KDD | TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. | Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf |
| 2019 | WWW | Addressing Trust Bias for Unbiased Learning-to-Rank. | Aman Agarwal, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork |
| 2019 | WWW | Personalized Online Spell Correction for Personal Search. | Jai Prakash Gupta, Zhen Qin, Michael Bendersky, Donald Metzler |
| 2019 | WWW | Semantic Text Matching for Long-Form Documents. | Jyun-Yu Jiang, Mingyang Zhang, Cheng Li, Michael Bendersky, Nadav Golbandi, Marc Najork |
| 2019 | SIGIR | Revisiting Approximate Metric Optimization in the Age of Deep Neural Networks. | Sebastian Bruch, Masrour Zoghi, Michael Bendersky, Marc Najork |
| 2019 | SIGIR | Multi-view Embedding-based Synonyms for Email Search. | Cheng Li, Mingyang Zhang, Michael Bendersky, Hongbo Deng, Donald Metzler, Marc Najork |
| 2019 | SIGIR | Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning. | Claudio Lucchese, Franco Maria Nardini, Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang, Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke |
| 2019 | SIGIR | Domain Adaptation for Enterprise Email Search. | Brandon Tran, Maryam Karimzadehgan, Rama Kumar Pasumarthi, Michael Bendersky, Donald Metzler |
| 2018 | CIKM | Multi-Task Learning for Email Search Ranking with Auxiliary Query Clustering. | Jiaming Shen, Maryam Karimzadehgan, Michael Bendersky, Zhen Qin, Donald Metzler |
| 2018 | CIKM | The LambdaLoss Framework for Ranking Metric Optimization. | Xuanhui Wang, Cheng Li, Nadav Golbandi, Michael Bendersky, Marc Najork |
| 2018 | IJCAI | Learning with Sparse and Biased Feedback for Personal Search. | Michael Bendersky, Xuanhui Wang, Marc Najork, Donald Metzler |
| 2018 | SIGIR | Semantic Location in Email Query Suggestion. | John Foley, Mingyang Zhang, Michael Bendersky, Marc Najork |
| 2018 | WSDM | Position Bias Estimation for Unbiased Learning to Rank in Personal Search. | Xuanhui Wang, Nadav Golbandi, Michael Bendersky, Donald Metzler, Marc Najork |
| 2017 | WWW | Situational Context for Ranking in Personal Search. | Hamed Zamani, Michael Bendersky, Xuanhui Wang, Mingyang Zhang |
| 2017 | WSDM | Learning from User Interactions in Personal Search via Attribute Parameterization. | Michael Bendersky, Xuanhui Wang, Donald Metzler, Marc Najork |
| 2017 | WSDM | Related Event Discovery. | Cheng Li, Michael Bendersky, Vijay Garg, Sujith Ravi |
| 2016 | SIGIR | Learning to Rank with Selection Bias in Personal Search. | Xuanhui Wang, Michael Bendersky, Donald Metzler, Marc Najork |
| 2016 | WSDM | Hierarchical Label Propagation and Discovery for Machine Generated Email. | James B. Wendt, Michael Bendersky, Lluis Garcia Pueyo, Vanja Josifovski, Balint Miklos, Ivo Krka, Amitabh Saikia, Jie Yang, Marc-Allen Cartright, Sujith Ravi |
| 2015 | SIGIR | Learning to Extract Local Events from the Web. | John Foley, Michael Bendersky, Vanja Josifovski |
| 2015 | SIGIR | Information Retrieval with Verbose Queries. | Manish Gupta, Michael Bendersky |
| 2014 | KDD | Up next: retrieval methods for large scale related video suggestion. | Michael Bendersky, Lluis Garcia Pueyo, Jeremiah J. Harmsen, Vanja Josifovski, Dima Lepikhin |
| 2013 | ECIR | Two-Stage Learning to Rank for Information Retrieval. | Van Dang, Michael Bendersky, W. Bruce Croft |
| 2012 | SIGIR | Modeling higher-order term dependencies in information retrieval using query hypergraphs. | Michael Bendersky, W. Bruce Croft |
| 2012 | WSDM | Effective query formulation with multiple information sources. | Michael Bendersky, Donald Metzler, W. Bruce Croft |
| 2011 | ACL | Joint Annotation of Search Queries. | Michael Bendersky, W. Bruce Croft, David A. Smith |
| 2011 | SIGIR | Parameterized concept weighting in verbose queries. | Michael Bendersky, Donald Metzler, W. Bruce Croft |
| 2011 | WSDM | Quality-biased ranking of web documents. | Michael Bendersky, W. Bruce Croft, Yanlei Diao |
| 2010 | CIKM | Structural annotation of search queries using pseudo-relevance feedback. | Michael Bendersky, W. Bruce Croft, David A. Smith |
| 2010 | WWW | The anatomy of an ad: structured indexing and retrieval for sponsored search. | Michael Bendersky, Evgeniy Gabrilovich, Vanja Josifovski, Donald Metzler |
| 2010 | SIGIR | Learning to rank query reformulations. | Van Dang, Michael Bendersky, W. Bruce Croft |
| 2010 | WSDM | Learning concept importance using a weighted dependence model. | Michael Bendersky, Donald Metzler, W. Bruce Croft |
| 2009 | CIKM | Utilizing inter-passage and inter-document similarities for re-ranking search results. | Eyal Krikon, Oren Kurland, Michael Bendersky |
| 2009 | SIGIR | Two-stage query segmentation for information retrieval. | Michael Bendersky, W. Bruce Croft, David A. Smith |
| 2009 | WSDM | Finding text reuse on the web. | Michael Bendersky, W. Bruce Croft |
| 2009 | WSDM | Analysis of long queries in a large scale search log. | Michael Bendersky, W. Bruce Croft |
| 2008 | ECIR | Utilizing Passage-Based Language Models for Document Retrieval. | Michael Bendersky, Oren Kurland |
| 2008 | SIGIR | Discovering key concepts in verbose queries. | Michael Bendersky, W. Bruce Croft |
| 2008 | SIGIR | Re-ranking search results using document-passage graphs. | Michael Bendersky, Oren Kurland |