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2020 – today
- 2025
[i66]Alireza Salemi, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Weize Kong, Tao Chen, Zhuowan Li, Michael Bendersky, Hamed Zamani:
Reasoning-Enhanced Self-Training for Long-Form Personalized Text Generation. CoRR abs/2501.04167 (2025)- 2024
- [c110]Weize Kong, Spurthi Amba Hombaiah, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky:
PRewrite: Prompt Rewriting with Reinforcement Learning. ACL (Short Papers) 2024: 594-601 - [c109]Alireza Salemi, Sheshera Mysore, Michael Bendersky, Hamed Zamani:
LaMP: When Large Language Models Meet Personalization. ACL (1) 2024: 7370-7392 - [c108]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:
Predicting Text Preference Via Structured Comparative Reasoning. ACL (1) 2024: 10040-10060 - [c107]Zixuan Ke, Weize Kong, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky:
Bridging the Preference Gap between Retrievers and LLMs. ACL (1) 2024: 10438-10451 - [c106]Yue Yu, Jiaming Shen, Tianqi Liu, Zhen Qin, Jing Nathan Yan, Jialu Liu, Chao Zhang, Michael Bendersky:
Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning. ACL (1) 2024: 14002-14024 - [c105]Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Haorui Wang, Zhen Qin, Feng Han, Jialu Liu, Simon Baumgartner, Michael Bendersky, Chao Zhang:
PLaD: Preference-based Large Language Model Distillation with Pseudo-Preference Pairs. ACL (Findings) 2024: 15623-15636 - [c104]Le Yan, Zhen Qin, Honglei Zhuang, Rolf Jagerman, Xuanhui Wang, Michael Bendersky, Harrie Oosterhuis:
Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing. EMNLP 2024: 410-423 - [c103]Zhuowan Li, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky:
Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach. EMNLP (Industry Track) 2024: 881-893 - [c102]Jiaming Shen, Tianqi Liu, Jialu Liu, Zhen Qin, Jay Pavagadhi, Simon Baumgartner, Michael Bendersky:
Multilingual Fine-Grained News Headline Hallucination Detection. EMNLP (Findings) 2024: 7862-7875 - [c101]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:
Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity. ICML 2024 - [c100]Harrie Oosterhuis
, Rolf Jagerman, Zhen Qin, Xuanhui Wang, Michael Bendersky:
Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I. KDD 2024: 2307-2317 - [c99]Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Jialu Liu, Michael Bendersky, Marc Najork, Chao Zhang:
Knowledge Distillation with Perturbed Loss: From a Vanilla Teacher to a Proxy Teacher. KDD 2024: 4278-4289 - [c98]Honglei Zhuang, Zhen Qin, Kai Hui, Junru Wu, Le Yan, Xuanhui Wang, Michael Bendersky:
Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels. NAACL (Short Papers) 2024: 358-370 - [c97]Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Le Yan, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, Michael Bendersky:
Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting. NAACL-HLT (Findings) 2024: 1504-1518 - [c96]Aditi Chaudhary, Karthik Raman, Michael Bendersky:
It's All Relative! - A Synthetic Query Generation Approach for Improving Zero-Shot Relevance Prediction. NAACL-HLT (Findings) 2024: 1645-1664 - [c95]Kazuma Hashimoto, Karthik Raman, Michael Bendersky:
Take One Step at a Time to Know Incremental Utility of Demonstration: An Analysis on Reranking for Few-Shot In-Context Learning. NAACL-HLT 2024: 3973-3990 - [c94]Minghan Li, Honglei Zhuang, Kai Hui, Zhen Qin, Jimmy Lin, Rolf Jagerman, Xuanhui Wang, Michael Bendersky:
Can Query Expansion Improve Generalization of Strong Cross-Encoder Rankers? SIGIR 2024: 2321-2326 - [c93]Hamed Zamani, Michael Bendersky:
Stochastic RAG: End-to-End Retrieval-Augmented Generation through Expected Utility Maximization. SIGIR 2024: 2641-2646 - [c92]Michael Bendersky, Cheng Li, Qiaozhu Mei, Vanessa Murdock, Jie Tang, Hongning Wang, Hamed Zamani, Mingyang Zhang, Xingjian Zhang:
The Second Workshop on Large Language Models for Individuals, Groups, and Society. SIGIR 2024: 3062-3064 - [c91]Michael Bendersky, Cheng Li, Qiaozhu Mei, Vanessa Murdock, Jie Tang, Hongning Wang, Hamed Zamani, Mingyang Zhang:
WSDM 2024 Workshop on Large Language Models for Individuals, Groups, and Society. WSDM 2024: 1206-1207 - [c90]Cheng Li, Mingyang Zhang, Qiaozhu Mei, Weize Kong, Michael Bendersky:
Learning to Rewrite Prompts for Personalized Text Generation. WWW 2024: 3367-3378 - [p1]Michael Bendersky, Donald Metzler, Marc Najork, Xuanhui Wang:
Searching Personal Collections. Information Retrieval: Advanced Topics and Techniques 2024: 515-538 - [i65]Zixuan Ke, Weize Kong, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky:
Bridging the Preference Gap between Retrievers and LLMs. CoRR abs/2401.06954 (2024) - [i64]Weize Kong, Spurthi Amba Hombaiah, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky:
PRewrite: Prompt Rewriting with Reinforcement Learning. CoRR abs/2401.08189 (2024) - [i63]Tao Chen, Siqi Zuo, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky:
Unlocking the 'Why' of Buying: Introducing a New Dataset and Benchmark for Purchase Reason and Post-Purchase Experience. CoRR abs/2402.13417 (2024) - [i62]Le Yan, Zhen Qin, Honglei Zhuang, Rolf Jagerman, Xuanhui Wang, Michael Bendersky, Harrie Oosterhuis:
Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing. CoRR abs/2404.11791 (2024) - [i61]Hamed Zamani, Michael Bendersky:
Stochastic RAG: End-to-End Retrieval-Augmented Generation through Expected Utility Maximization. CoRR abs/2405.02816 (2024) - [i60]Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Haorui Wang, Zhen Qin, Feng Han, Jialu Liu, Simon Baumgartner, Michael Bendersky, Chao Zhang:
PLaD: Preference-based Large Language Model Distillation with Pseudo-Preference Pairs. CoRR abs/2406.02886 (2024) - [i59]Harrie Oosterhuis, Rolf Jagerman, Zhen Qin, Xuanhui Wang, Michael Bendersky:
Reliable Confidence Intervals for Information Retrieval Evaluation Using Generative A.I. CoRR abs/2407.02464 (2024) - [i58]Haoyang Wen, Honglei Zhuang, Hamed Zamani, Alexander Hauptmann, Michael Bendersky:
Multimodal Reranking for Knowledge-Intensive Visual Question Answering. CoRR abs/2407.12277 (2024) - [i57]Jiaming Shen, Tianqi Liu, Jialu Liu, Zhen Qin, Jay Pavagadhi, Simon Baumgartner, Michael Bendersky:
Multilingual Fine-Grained News Headline Hallucination Detection. CoRR abs/2407.15975 (2024) - [i56]Jiaming Shen, Ran Xu, Yennie Jun, Zhen Qin, Tianqi Liu, Carl Yang, Yi Liang, Simon Baumgartner, Michael Bendersky:
Boosting Reward Model with Preference-Conditional Multi-Aspect Synthetic Data Generation. CoRR abs/2407.16008 (2024) - [i55]Zhuowan Li, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Michael Bendersky:
Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach. CoRR abs/2407.16833 (2024) - [i54]Zhenrui Yue, Honglei Zhuang, Aijun Bai, Kai Hui, Rolf Jagerman, Hansi Zeng, Zhen Qin, Dong Wang, Xuanhui Wang, Michael Bendersky:
Inference Scaling for Long-Context Retrieval Augmented Generation. CoRR abs/2410.04343 (2024) - [i53]Yi Liang, You Wu, Honglei Zhuang, Li Chen, Jiaming Shen, Yiling Jia, Zhen Qin, Sumit Sanghai, Xuanhui Wang, Carl Yang, Michael Bendersky:
Integrating Planning into Single-Turn Long-Form Text Generation. CoRR abs/2410.06203 (2024) - [i52]Jianhong Tu, Zhuohao Ni, Nicholas Crispino, Zihao Yu, Michael Bendersky, Beliz Gunel, Ruoxi Jia, Xin Liu, Lingjuan Lyu, Dawn Song, Chenguang Wang:
MLAN: Language-Based Instruction Tuning Improves Zero-Shot Generalization of Multimodal Large Language Models. CoRR abs/2411.10557 (2024) - [i51]Michael Bendersky, Donald Metzler, Marc Najork, Xuanhui Wang:
Searching Personal Collections. CoRR abs/2412.12330 (2024) - 2023
- [j10]Eyal Brill, Michael Bendersky:
A Graphical Calibration Method for a Water Quality Model Considering Process Variability Versus Delay Time: Theory and a Case Study. Comput. 11(10): 200 (2023) - [c89]Jeffrey M. Dudek, Weize Kong, Cheng Li, Mingyang Zhang, Michael Bendersky:
Learning Sparse Lexical Representations Over Specified Vocabularies for Retrieval. CIKM 2023: 3865-3869 - [c88]Aijun Bai, Rolf Jagerman, Zhen Qin, Le Yan, Pratyush Kar, Bing-Rong Lin, Xuanhui Wang, Michael Bendersky, Marc Najork:
Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance. CIKM 2023: 4502-4508 - [c87]Aditi Chaudhary, Karthik Raman, Krishna Srinivasan, Kazuma Hashimoto, Mike Bendersky, Marc Najork:
Exploring the Viability of Synthetic Query Generation for Relevance Prediction. eCom@SIGIR 2023 - [c86]Spurthi Amba Hombaiah, Tao Chen, Mingyang Zhang, Michael Bendersky, Marc Najork, Matt Colen, Sergey Levi, Vladimir Ofitserov, Tanvir Amin:
Creator Context for Tweet Recommendation. EMNLP (Industry Track) 2023: 353-363 - [c85]Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky:
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. KDD 2023: 3737-3749 - [c84]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:
End-to-End Query Term Weighting. KDD 2023: 4778-4786 - [c83]Yunan Zhang, Le Yan, Zhen Qin, Honglei Zhuang, Jiaming Shen, Xuanhui Wang, Michael Bendersky, Marc Najork:
Towards Disentangling Relevance and Bias in Unbiased Learning to Rank. KDD 2023: 5618-5627 - [c82]Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky:
Learning List-Level Domain-Invariant Representations for Ranking. NeurIPS 2023 - [c81]Hamed Zamani, Michael Bendersky:
Multivariate Representation Learning for Information Retrieval. SIGIR 2023: 163-173 - [c80]Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, Michael Bendersky:
RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses. SIGIR 2023: 2308-2313 - [c79]Weize Kong, Jeffrey M. Dudek, Cheng Li, Mingyang Zhang, Michael Bendersky:
SparseEmbed: Learning Sparse Lexical Representations with Contextual Embeddings for Retrieval. SIGIR 2023: 2399-2403 - [c78]Qingyao Ai, Xuanhui Wang, Michael Bendersky:
Metric-agnostic Ranking Optimization. SIGIR 2023: 2669-2680 - [c77]Michael Bendersky, Danqi Chen, Fernando Diaz, Hamed Zamani:
SIGIR 2023 Workshop on Retrieval Enhanced Machine Learning (REML @ SIGIR 2023). SIGIR 2023: 3468-3471 - [c76]Xiang Deng, Vasilisa Bashlovkina, Feng Han, Simon Baumgartner, Michael Bendersky:
What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis. WWW (Companion Volume) 2023: 107-110 - [c75]Cheng Li, Yaping Qi, Hayk Zakaryan, Mingyang Zhang, Michael Bendersky, Yonghua Wu, Marc Najork:
Job Type Extraction for Service Businesses. WWW (Companion Volume) 2023: 401-405 - [c74]Xiang Deng, Vasilisa Bashlovkina, Feng Han, Simon Baumgartner, Michael Bendersky:
LLMs to the Moon? Reddit Market Sentiment Analysis with Large Language Models. WWW (Companion Volume) 2023: 1014-1019 - [c73]Jiaming Shen, Jialu Liu, Daniel Finnie, Negar Rahmati, Mike Bendersky, Marc Najork:
"Why is this misleading?": Detecting News Headline Hallucinations with Explanations. WWW 2023: 1662-1672 - [i50]Jiaming Shen, Jialu Liu, Daniel Finnie, Negar Rahmati, Michael Bendersky, Marc Najork:
"Why is this misleading?": Detecting News Headline Hallucinations with Explanations. CoRR abs/2302.05852 (2023) - [i49]Qingyao Ai, Xuanhui Wang, Michael Bendersky:
Metric-agnostic Ranking Optimization. CoRR abs/2304.08062 (2023) - [i48]Alireza Salemi, Sheshera Mysore, Michael Bendersky, Hamed Zamani:
LaMP: When Large Language Models Meet Personalization. CoRR abs/2304.11406 (2023) - [i47]Hamed Zamani, Michael Bendersky:
Multivariate Representation Learning for Information Retrieval. CoRR abs/2304.14522 (2023) - [i46]Rolf Jagerman, Honglei Zhuang, Zhen Qin, Xuanhui Wang, Michael Bendersky:
Query Expansion by Prompting Large Language Models. CoRR abs/2305.03653 (2023) - [i45]Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Jialu Liu, Michael Bendersky, Marc Najork, Chao Zhang:
Do Not Blindly Imitate the Teacher: Using Perturbed Loss for Knowledge Distillation. CoRR abs/2305.05010 (2023) - [i44]Aditi Chaudhary, Karthik Raman, Krishna Srinivasan, Kazuma Hashimoto, Mike Bendersky, Marc Najork:
Exploring the Viability of Synthetic Query Generation for Relevance Prediction. CoRR abs/2305.11944 (2023) - [i43]Le Yan, Zhen Qin, Gil I. Shamir, Dong Lin, Xuanhui Wang, Mike Bendersky:
Learning to Rank when Grades Matter. CoRR abs/2306.08650 (2023) - [i42]Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, Michael Bendersky:
Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting. CoRR abs/2306.17563 (2023) - [i41]Vasilisa Bashlovkina, Riley Matthews, Zhaobin Kuang, Simon Baumgartner, Michael Bendersky:
SMILE: Evaluation and Domain Adaptation for Social Media Language Understanding. CoRR abs/2307.00135 (2023) - [i40]Cheng Li, Mingyang Zhang, Qiaozhu Mei, Yaqing Wang, Spurthi Amba Hombaiah, Yi Liang, Michael Bendersky:
Teach LLMs to Personalize - An Approach inspired by Writing Education. CoRR abs/2308.07968 (2023) - [i39]Lingyu Gao, Aditi Chaudhary, Krishna Srinivasan, Kazuma Hashimoto, Karthik Raman, Michael Bendersky:
Ambiguity-Aware In-Context Learning with Large Language Models. CoRR abs/2309.07900 (2023) - [i38]Cheng Li, Mingyang Zhang, Qiaozhu Mei, Weize Kong, Michael Bendersky:
Automatic Prompt Rewriting for Personalized Text Generation. CoRR abs/2310.00152 (2023) - [i37]Yaqing Wang, Jiepu Jiang, Mingyang Zhang, Cheng Li, Yi Liang, Qiaozhu Mei, Michael Bendersky:
Automated Evaluation of Personalized Text Generation using Large Language Models. CoRR abs/2310.11593 (2023) - [i36]Yaqing Wang, Jialin Wu, Tanmaya Dabral, Jiageng Zhang, Geoff Brown, Chun-Ta Lu, Frederick Liu, Yi Liang, Bo Pang, Michael Bendersky, Radu Soricut:
Non-Intrusive Adaptation: Input-Centric Parameter-efficient Fine-Tuning for Versatile Multimodal Modeling. CoRR abs/2310.12100 (2023) - [i35]Honglei Zhuang, Zhen Qin, Kai Hui, Junru Wu, Le Yan, Xuanhui Wang, Michael Bendersky:
Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels. CoRR abs/2310.14122 (2023) - [i34]Yue Yu, Jiaming Shen, Tianqi Liu, Zhen Qin, Jing Nathan Yan, Jialu Liu, Chao Zhang, Michael Bendersky:
Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning. CoRR abs/2311.07099 (2023) - [i33]Aditi Chaudhary, Karthik Raman, Michael Bendersky:
It's All Relative! - A Synthetic Query Generation Approach for Improving Zero-Shot Relevance Prediction. CoRR abs/2311.07930 (2023) - [i32]Jing Nathan Yan, Tianqi Liu, Justin T. Chiu, Jiaming Shen, Zhen Qin, Yue Yu, Yao Zhao, Charu Lakshmanan, Yair Kurzion, Alexander M. Rush, Jialu Liu, Michael Bendersky:
On What Basis? Predicting Text Preference Via Structured Comparative Reasoning. CoRR abs/2311.08390 (2023) - [i31]Minghan Li, Honglei Zhuang, Kai Hui, Zhen Qin, Jimmy Lin, Rolf Jagerman, Xuanhui Wang, Michael Bendersky:
Generate, Filter, and Fuse: Query Expansion via Multi-Step Keyword Generation for Zero-Shot Neural Rankers. CoRR abs/2311.09175 (2023) - [i30]Kazuma Hashimoto, Karthik Raman, Michael Bendersky:
Take One Step at a Time to Know Incremental Utility of Demonstration: An Analysis on Reranking for Few-Shot In-Context Learning. CoRR abs/2311.09619 (2023) - [i29]Spurthi Amba Hombaiah, Tao Chen, Mingyang Zhang, Michael Bendersky, Marc Najork, Matt Colen, Sergey Levi, Vladimir Ofitserov, Tanvir Amin:
Creator Context for Tweet Recommendation. CoRR abs/2311.17650 (2023) - 2022
- [c72]Tao Chen, Mingyang Zhang, Jing Lu, Michael Bendersky, Marc Najork:
Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models. ECIR (1) 2022: 95-110 - [c71]Krishna Srinivasan, Karthik Raman, Anupam Samanta, Lingrui Liao, Luca Bertelli, Michael Bendersky:
QUILL: Query Intent with Large Language Models using Retrieval Augmentation and Multi-stage Distillation. EMNLP (Industry Track) 2022: 492-501 - [c70]Hamed Zamani, Michael Bendersky, Donald Metzler, Honglei Zhuang, Xuanhui Wang:
Stochastic Retrieval-Conditioned Reranking. ICTIR 2022: 81-91 - [c69]Rolf Jagerman, Xuanhui Wang, Honglei Zhuang, Zhen Qin, Michael Bendersky, Marc Najork:
Rax: Composable Learning-to-Rank Using JAX. KDD 2022: 3051-3060 - [c68]Weize Kong, Swaraj Khadanga, Cheng Li, Shaleen Kumar Gupta, Mingyang Zhang, Wensong Xu, Michael Bendersky:
Multi-Aspect Dense Retrieval. KDD 2022: 3178-3186 - [c67]Le Yan, Zhen Qin, Xuanhui Wang, Michael Bendersky, Marc Najork:
Scale Calibration of Deep Ranking Models. KDD 2022: 4300-4309 - [c66]Rolf Jagerman, Zhen Qin, Xuanhui Wang, Michael Bendersky, Marc Najork:
On Optimizing Top-K Metrics for Neural Ranking Models. SIGIR 2022: 2303-2307 - [c65]Le Yan, Zhen Qin, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork:
Revisiting Two-tower Models for Unbiased Learning to Rank. SIGIR 2022: 2410-2414 - [c64]Hamed Zamani, Fernando Diaz, Mostafa Dehghani, Donald Metzler, Michael Bendersky:
Retrieval-Enhanced Machine Learning. SIGIR 2022: 2875-2886 - [c63]Michael Bendersky, Xuanhui Wang, Marc Najork, Donald Metzler:
Search and Discovery in Personal Email Collections. WSDM 2022: 1617-1619 - [i28]Tao Chen, Mingyang Zhang, Jing Lu, Michael Bendersky, Marc Najork:
Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models. CoRR abs/2201.10582 (2022) - [i27]Hamed Zamani, Fernando Diaz, Mostafa Dehghani, Donald Metzler, Michael Bendersky:
Retrieval-Enhanced Machine Learning. CoRR abs/2205.01230 (2022) - [i26]Kai Hui, Tao Chen, Zhen Qin, Honglei Zhuang, Fernando Diaz, Mike Bendersky, Don Metzler:
Retrieval Augmentation for T5 Re-ranker using External Sources. CoRR abs/2210.05145 (2022) - [i25]Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, Michael Bendersky:
RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses. CoRR abs/2210.10634 (2022) - [i24]Krishna Srinivasan, Karthik Raman, Anupam Samanta, Lingrui Liao, Luca Bertelli, Mike Bendersky:
QUILL: Query Intent with Large Language Models using Retrieval Augmentation and Multi-stage Distillation. CoRR abs/2210.15718 (2022) - [i23]Aijun Bai, Rolf Jagerman, Zhen Qin, Pratyush Kar, Bing-Rong Lin, Xuanhui Wang, Michael Bendersky, Marc Najork:
Regression Compatible Listwise Objectives for Calibrated Ranking. CoRR abs/2211.01494 (2022) - [i22]Ruicheng Xian, Honglei Zhuang, Zhen Qin, Hamed Zamani, Jing Lu, Ji Ma, Kai Hui, Han Zhao, Xuanhui Wang, Michael Bendersky:
Learning List-Level Domain-Invariant Representations for Ranking. CoRR abs/2212.10764 (2022) - [i21]Xiang Deng, Vasilisa Bashlovkina, Feng Han, Simon Baumgartner, Michael Bendersky:
What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysis. CoRR abs/2212.11311 (2022) - [i20]Yunan Zhang, Le Yan, Zhen Qin, Honglei Zhuang, Jiaming Shen, Xuanhui Wang, Michael Bendersky, Marc Najork:
Towards Disentangling Relevance and Bias in Unbiased Learning to Rank. CoRR abs/2212.13937 (2022) - 2021
- [j9]Michael Bendersky, Xuanhui Wang, Marc Najork, Donald Metzler:
Search and Discovery in Personal Email Collections. Found. Trends Inf. Retr. 15(1): 1-133 (2021) - [j8]Michael Bendersky, Israel David, Dor Elboim:
Fire support with Gaussian estimation of environmental conditions based on single or multiple target registration. J. Oper. Res. Soc. 72(9): 2112-2121 (2021) - [c62]Chen Qu, Weize Kong, Liu Yang, Mingyang Zhang, Michael Bendersky, Marc Najork:
Natural Language Understanding with Privacy-Preserving BERT. CIKM 2021: 1488-1497 - [c61]Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork:
Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees? ICLR 2021 - [c60]Honglei Zhuang, Zhen Qin, Shuguang Han, Xuanhui Wang, Michael Bendersky, Marc Najork:
Ensemble Distillation for BERT-Based Ranking Models. ICTIR 2021: 131-136 - [c59]Spurthi Amba Hombaiah, Tao Chen, Mingyang Zhang, Michael Bendersky, Marc Najork:
Dynamic Language Models for Continuously Evolving Content. KDD 2021: 2514-2524 - [c58]Zhen Qin, Honglei Zhuang, Rolf Jagerman, Xinyu Qian, Po Hu, Dan Chary Chen, Xuanhui Wang, Michael Bendersky, Marc Najork:
Bootstrapping Recommendations at Chrome Web Store. KDD 2021: 3483-3491 - [c57]Krishna Srinivasan, Karthik Raman, Jiecao Chen, Michael Bendersky, Marc Najork:
WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning. SIGIR 2021: 2443-2449 - [c56]Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Alexander Grushetsky, Yonghui Wu, Petr Mitrichev, Ethan Sterling, Nathan Bell, Walker Ravina, Hai Qian:
Interpretable Ranking with Generalized Additive Models. WSDM 2021: 499-507 - [c55]Rolf Jagerman, Weize Kong, Rama Kumar Pasumarthi, Zhen Qin, Michael Bendersky, Marc Najork:
Improving Cloud Storage Search with User Activity. WSDM 2021: 508-516 - [c54]Le Yan, Zhen Qin, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky:
Diversification-Aware Learning to Rank using Distributed Representation. WWW 2021: 127-136 - [c53]Honglei Zhuang, Zhen Qin, Xuanhui Wang, Michael Bendersky, Xinyu Qian, Po Hu, Dan Chary Chen:
Cross-Positional Attention for Debiasing Clicks. WWW 2021: 788-797 - [i19]Krishna Srinivasan, Karthik Raman, Jiecao Chen, Michael Bendersky, Marc Najork:
WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning. CoRR abs/2103.01913 (2021) - [i18]Chen Qu, Weize Kong, Liu Yang, Mingyang Zhang, Michael Bendersky, Marc Najork:
Privacy-Adaptive BERT for Natural Language Understanding. CoRR abs/2104.07504 (2021) - [i17]Te-Lin Wu, Cheng Li, Mingyang Zhang, Tao Chen, Spurthi Amba Hombaiah, Michael Bendersky:
LAMPRET: Layout-Aware Multimodal PreTraining for Document Understanding. CoRR abs/2104.08405 (2021) - [i16]Spurthi Amba Hombaiah, Tao Chen, Mingyang Zhang, Michael Bendersky, Marc Najork:
Dynamic Language Models for Continuously Evolving Content. CoRR abs/2106.06297 (2021) - [i15]Zhen Qin, Le Yan, Yi Tay, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork:
Born Again Neural Rankers. CoRR abs/2109.15285 (2021) - [i14]Nan Wang, Zhen Qin, Le Yan, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork:
Rank4Class: A Ranking Formulation for Multiclass Classification. CoRR abs/2112.09727 (2021) - 2020
- [c52]Liu Yang, Mingyang Zhang, Cheng Li, Michael Bendersky, Marc Najork:
Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Long-Form Document Matching. CIKM 2020: 1725-1734 - [c51]Jiecao Chen, Liu Yang, Karthik Raman, Michael Bendersky, Jung-Jung Yeh, Yun Zhou, Marc Najork, Danyang Cai, Ehsan Emadzadeh:
DiPair: Fast and Accurate Distillation for Trillion-ScaleText Matching and Pair Modeling. EMNLP (Findings) 2020: 2925-2937 - [c50]Rama Kumar Pasumarthi, Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork:
Permutation Equivariant Document Interaction Network for Neural Learning to Rank. ICTIR 2020: 145-148 - [c49]Weize Kong, Michael Bendersky, Marc Najork, Brandon Vargo, Mike Colagrosso:
Learning to Cluster Documents into Workspaces Using Large Scale Activity Logs. KDD 2020: 2416-2424 - [c48]Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Marc Najork:
Feature Transformation for Neural Ranking Models. SIGIR 2020: 1649-1652 - [c47]Sebastian Bruch, Shuguang Han, Michael Bendersky, Marc Najork:
A Stochastic Treatment of Learning to Rank Scoring Functions. WSDM 2020: 61-69 - [c46]Shuguang Han, Michael Bendersky, Przemek Gajda, Sergey Novikov, Marc Najork, Bernhard Brodowsky, Alexandrin Popescul:
Adversarial Bandits Policy for Crawling Commercial Web Content. WWW 2020: 407-417 - [c45]Zhen Qin, Zhongliang Li, Michael Bendersky, Donald Metzler:
Matching Cross Network for Learning to Rank in Personal Search. WWW 2020: 2835-2841 - [i13]Shuguang Han, Xuanhui Wang, Mike Bendersky, Marc Najork:
Learning-to-Rank with BERT in TF-Ranking. CoRR abs/2004.08476 (2020) - [i12]Liu Yang, Mingyang Zhang, Cheng Li, Michael Bendersky, Marc Najork:
Beyond 512 Tokens: Siamese Multi-depth Transformer-based Hierarchical Encoder for Document Matching. CoRR abs/2004.12297 (2020) - [i11]Honglei Zhuang, Xuanhui Wang, Michael Bendersky, Alexander Grushetsky, Yonghui Wu, Petr Mitrichev, Ethan Sterling, Nathan Bell, Walker Ravina, Hai Qian:
Interpretable Learning-to-Rank with Generalized Additive Models. CoRR abs/2005.02553 (2020) - [i10]Michael Bendersky, Honglei Zhuang, Ji Ma, Shuguang Han, Keith B. Hall, Ryan T. McDonald:
RRF102: Meeting the TREC-COVID Challenge with a 100+ Runs Ensemble. CoRR abs/2010.00200 (2020) - [i9]Saar Kuzi, Mingyang Zhang, Cheng Li, Michael Bendersky, Marc Najork:
Leveraging Semantic and Lexical Matching to Improve the Recall of Document Retrieval Systems: A Hybrid Approach. CoRR abs/2010.01195 (2020) - [i8]Jiecao Chen, Liu Yang, Karthik Raman, Michael Bendersky, Jung-Jung Yeh, Yun Zhou, Marc Najork, Danyang Cai, Ehsan Emadzadeh:
DiPair: Fast and Accurate Distillation for Trillion-Scale Text Matching and Pair Modeling. CoRR abs/2010.03099 (2020)
2010 – 2019
- 2019
- [c44]Sebastian Bruch, Xuanhui Wang, Michael Bendersky, Marc Najork:
An Analysis of the Softmax Cross Entropy Loss for Learning-to-Rank with Binary Relevance. ICTIR 2019: 75-78 - [c43]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 - [c42]Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang:
Neural Learning to Rank using TensorFlow Ranking: A Hands-on Tutorial. ICTIR 2019: 253-254 - [c41]Rama Kumar Pasumarthi, Sebastian Bruch, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf:
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. KDD 2019: 2970-2978 - [c40]Brandon Tran, Maryam Karimzadehgan, Rama Kumar Pasumarthi, Michael Bendersky, Donald Metzler:
Domain Adaptation for Enterprise Email Search. SIGIR 2019: 25-34 - [c39]Cheng Li, Mingyang Zhang, Michael Bendersky, Hongbo Deng, Donald Metzler, Marc Najork:
Multi-view Embedding-based Synonyms for Email Search. SIGIR 2019: 575-584 - [c38]Sebastian Bruch, Masrour Zoghi, Michael Bendersky, Marc Najork:
Revisiting Approximate Metric Optimization in the Age of Deep Neural Networks. SIGIR 2019: 1241-1244 - [c37]Claudio Lucchese, Franco Maria Nardini, Rama Kumar Pasumarthi, Sebastian Bruch, Michael Bendersky, Xuanhui Wang, Harrie Oosterhuis, Rolf Jagerman, Maarten de Rijke:
Learning to Rank in Theory and Practice: From Gradient Boosting to Neural Networks and Unbiased Learning. SIGIR 2019: 1419-1420 - [c36]Aman Agarwal, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork:
Addressing Trust Bias for Unbiased Learning-to-Rank. WWW 2019: 4-14 - [c35]Shuguang Han, Bernhard Brodowsky, Przemek Gajda, Sergey Novikov, Mike Bendersky, Marc Najork, Robin Dua, Alexandrin Popescul:
Predictive Crawling for Commercial Web Content. WWW 2019: 627-637 - [c34]Jyun-Yu Jiang, Mingyang Zhang, Cheng Li, Michael Bendersky, Nadav Golbandi, Marc Najork:
Semantic Text Matching for Long-Form Documents. WWW 2019: 795-806 - [c33]Jai Prakash Gupta, Zhen Qin, Michael Bendersky, Donald Metzler:
Personalized Online Spell Correction for Personal Search. WWW 2019: 2785-2791 - [i7]Brandon Tran, Maryam Karimzadehgan, Rama Kumar Pasumarthi, Michael Bendersky, Donald Metzler:
Domain Adaptation for Enterprise Email Search. CoRR abs/1906.07897 (2019) - [i6]Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork:
Self-Attentive Document Interaction Networks for Permutation Equivariant Ranking. CoRR abs/1910.09676 (2019) - 2018
- [c32]Xuanhui Wang, Cheng Li, Nadav Golbandi, Michael Bendersky, Marc Najork:
The LambdaLoss Framework for Ranking Metric Optimization. CIKM 2018: 1313-1322 - [c31]Jiaming Shen, Maryam Karimzadehgan, Michael Bendersky, Zhen Qin, Donald Metzler:
Multi-Task Learning for Email Search Ranking with Auxiliary Query Clustering. CIKM 2018: 2127-2135 - [c30]Michael Bendersky, Xuanhui Wang, Marc Najork, Donald Metzler:
Learning with Sparse and Biased Feedback for Personal Search. IJCAI 2018: 5219-5223 - [c29]John Foley, Mingyang Zhang, Michael Bendersky, Marc Najork:
Semantic Location in Email Query Suggestion. SIGIR 2018: 977-980 - [c28]Xuanhui Wang, Nadav Golbandi, Michael Bendersky, Donald Metzler, Marc Najork:
Position Bias Estimation for Unbiased Learning to Rank in Personal Search. WSDM 2018: 610-618 - [i5]Jiaming Shen, Maryam Karimzadehgan, Michael Bendersky, Zhen Qin, Donald Metzler:
Multi-Task Learning for Email Search Ranking with Auxiliary Query Clustering. CoRR abs/1809.05618 (2018) - [i4]Aman Agarwal, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork:
Offline Comparison of Ranking Functions using Randomized Data. CoRR abs/1810.05252 (2018) - [i3]Qingyao Ai, Xuanhui Wang, Nadav Golbandi, Michael Bendersky, Marc Najork:
Learning Groupwise Scoring Functions Using Deep Neural Networks. CoRR abs/1811.04415 (2018) - [i2]Rama Kumar Pasumarthi, Xuanhui Wang, Cheng Li, Sebastian Bruch, Michael Bendersky, Marc Najork, Jan Pfeifer, Nadav Golbandi, Rohan Anil, Stephan Wolf:
TF-Ranking: Scalable TensorFlow Library for Learning-to-Rank. CoRR abs/1812.00073 (2018) - 2017
- [c27]Cheng Li, Michael Bendersky, Vijay Garg, Sujith Ravi:
Related Event Discovery. WSDM 2017: 355-364 - [c26]Michael Bendersky, Xuanhui Wang, Donald Metzler, Marc Najork:
Learning from User Interactions in Personal Search via Attribute Parameterization. WSDM 2017: 791-799 - [c25]Hamed Zamani, Michael Bendersky, Xuanhui Wang, Mingyang Zhang:
Situational Context for Ranking in Personal Search. WWW 2017: 1531-1540 - 2016
- [j7]Michael Bendersky, Israel David:
Deciding kidney-offer admissibility dependent on patients' lifetime failure rate. Eur. J. Oper. Res. 251(2): 686-693 (2016) - [c24]Xuanhui Wang, Michael Bendersky, Donald Metzler, Marc Najork:
Learning to Rank with Selection Bias in Personal Search. SIGIR 2016: 115-124 - [c23]James B. Wendt, Michael Bendersky, Lluis Garcia Pueyo, Vanja Josifovski, Balint Miklos, Ivo Krka, Amitabh Saikia, Jie Yang, Marc-Allen Cartright, Sujith Ravi:
Hierarchical Label Propagation and Discovery for Machine Generated Email. WSDM 2016: 317-326 - [i1]Harrie Oosterhuis, Sujith Ravi, Michael Bendersky:
Semantic Video Trailers. CoRR abs/1609.01819 (2016) - 2015
- [j6]Manish Gupta, Michael Bendersky:
Information Retrieval with Verbose Queries. Found. Trends Inf. Retr. 9(3-4): 91-208 (2015) - [j5]Boris Kriheli, Eugene Levner, Michael Bendersky, Eduard H. Yakubov:
A Fast Algorithm for Scheduling Detection-and-Rescue Operations Based on Data from Wireless Sensor Networks. Res. Comput. Sci. 104: 9-21 (2015) - [c22]John Foley, Michael Bendersky, Vanja Josifovski:
Learning to Extract Local Events from the Web. SIGIR 2015: 423-432 - [c21]Manish Gupta, Michael Bendersky:
Information Retrieval with Verbose Queries. SIGIR 2015: 1121-1124 - 2014
- [c20]Michael Bendersky, Lluis Garcia Pueyo, Jeremiah J. Harmsen, Vanja Josifovski, Dima Lepikhin:
Up next: retrieval methods for large scale related video suggestion. KDD 2014: 1769-1778 - 2013
- [c19]Van Dang, Michael Bendersky, W. Bruce Croft:
Two-Stage Learning to Rank for Information Retrieval. ECIR 2013: 423-434 - 2012
- [j4]Michael Bendersky:
Information retrieval with query hypergraphs. SIGIR Forum 46(2): 111 (2012) - [c18]Michael Bendersky, David A. Smith:
A Dictionary of Wisdom and Wit: Learning to Extract Quotable Phrases. CLfL@NAACL-HLT 2012: 69-77 - [c17]Michael Bendersky, W. Bruce Croft:
Modeling higher-order term dependencies in information retrieval using query hypergraphs. SIGIR 2012: 941-950 - [c16]Michael Bendersky, Donald Metzler, W. Bruce Croft:
Effective query formulation with multiple information sources. WSDM 2012: 443-452 - 2011
- [c15]Michael Bendersky, W. Bruce Croft, David A. Smith:
Joint Annotation of Search Queries. ACL 2011: 102-111 - [c14]Michael Bendersky, Donald Metzler, W. Bruce Croft:
Parameterized concept weighting in verbose queries. SIGIR 2011: 605-614 - [c13]Michael Bendersky, W. Bruce Croft, Yanlei Diao:
Quality-biased ranking of web documents. WSDM 2011: 95-104 - 2010
- [j3]Michael Bendersky, Oren Kurland:
Utilizing passage-based language models for ad hoc document retrieval. Inf. Retr. 13(2): 157-187 (2010) - [j2]W. Bruce Croft, Michael Bendersky, Hang Li, Gu Xu:
Query representation and understanding workshop. SIGIR Forum 44(2): 48-53 (2010) - [j1]Eyal Krikon, Oren Kurland, Michael Bendersky:
Utilizing inter-passage and inter-document similarities for reranking search results. ACM Trans. Inf. Syst. 29(1): 3:1-3:28 (2010) - [c12]Michael Bendersky, W. Bruce Croft, David A. Smith:
Structural annotation of search queries using pseudo-relevance feedback. CIKM 2010: 1537-1540 - [c11]Van Dang, Michael Bendersky, W. Bruce Croft:
Learning to rank query reformulations. SIGIR 2010: 807-808 - [c10]Michael Bendersky, David Fisher, W. Bruce Croft:
TREC 2010 Web Track Notebook: Term Dependence, Spam Filtering and Quality Bias. TREC 2010 - [c9]Michael Bendersky, Donald Metzler, W. Bruce Croft:
Learning concept importance using a weighted dependence model. WSDM 2010: 31-40 - [c8]Michael Bendersky, Evgeniy Gabrilovich, Vanja Josifovski, Donald Metzler:
The anatomy of an ad: structured indexing and retrieval for sponsored search. WWW 2010: 101-110
2000 – 2009
- 2009
- [c7]Eyal Krikon, Oren Kurland, Michael Bendersky:
Utilizing inter-passage and inter-document similarities for re-ranking search results. CIKM 2009: 1597-1600 - [c6]Michael Bendersky, W. Bruce Croft, David A. Smith:
Two-stage query segmentation for information retrieval. SIGIR 2009: 810-811 - [c5]Michael Bendersky, W. Bruce Croft:
Analysis of long queries in a large scale search log. WSCD@WSDM 2009: 8-14 - [c4]Michael Bendersky, W. Bruce Croft:
Finding text reuse on the web. WSDM 2009: 262-271 - 2008
- [c3]Michael Bendersky, Oren Kurland:
Utilizing Passage-Based Language Models for Document Retrieval. ECIR 2008: 162-174 - [c2]Michael Bendersky, W. Bruce Croft:
Discovering key concepts in verbose queries. SIGIR 2008: 491-498 - [c1]Michael Bendersky, Oren Kurland:
Re-ranking search results using document-passage graphs. SIGIR 2008: 853-854
Coauthor Index
Donald Metzler
aka: Don Metzler
aka: Don Metzler
[c99] [p1] [i51] [c88] [c87] [c86] [c84] [c83] [c75] [c73] [i50] [i45] [i44] [i29] [c72] [c69] [c67] [c66] [c65] [c63] [i28] [i23] [i20] [j9] [c62] [c61] [c60] [c59] [c58] [c57] [c55] [i19] [i18] [i16] [i15] [i14] [c52] [c51] [c50] [c49] [c48] [c47] [c46] [i13] [i12] [i9] [i8] [c44] [c43] [c41] [c39] [c38] [c36] [c35] [c34] [i6] [c32] [c30] [c29] [c28] [i4] [i3] [i2] [c26] [c24]
[c104] [c100] [c98] [c97] [c94] [p1] [i62] [i59] [i54] [i53] [i51] [c88] [c83] [c82] [c80] [c78] [i49] [i46] [i43] [i42] [i35] [i31] [c70] [c69] [c67] [c66] [c65] [c63] [i25] [i23] [i22] [i20] [j9] [c61] [c60] [c58] [c56] [c54] [c53] [i15] [i14] [c50] [c48] [i13] [i11] [c44] [c43] [c42] [c41] [c37] [c36] [i6] [c32] [c30] [c28] [i4] [i3] [i2] [c26] [c25] [c24]
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