| 2026 | ACL | WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback. | Taiwei Shi, Zhuoer Wang, Longqi Yang, Ying-Chun Lin, Zexue He, Mengting Wan, Pei Zhou, Sujay Kumar Jauhar, Sihao Chen, Shan Xia, Hongfei Zhang, Jieyu Zhao, Xiaofeng Xu, Xia Song, Jennifer Neville |
| 2025 | ACL | GenTool: Enhancing Tool Generalization in Language Models through Zero-to-One and Weak-to-Strong Simulation. | Jie He, Jennifer Neville, Mengting Wan, Longqi Yang, Hui Liu, Xiaofeng Xu, Xia Song, Jeff Z. Pan, Pei Zhou |
| 2025 | EMNLP | Group Preference Alignment: Customizing LLM Responses from In-Situ Conversations Only When Needed. | Ishani Mondal, Jack W. Stokes, Sujay Kumar Jauhar, Longqi Yang, Mengting Wan, Xiaofeng Xu, Xia Song, Jordan Lee Boyd-Graber, Jennifer Neville |
| 2025 | ICLR | Node Similarities under Random Projections: Limits and Pathological Cases. | Tvrtko Tadic, Cassiano O. Becker, Jennifer Neville |
| 2025 | SIGIR | Researchy Questions: A Dataset of Multi-Perspective, Decompositional Questions for Deep Research. | Corbin Rosset, Ho-Lam Chung, Guanghui Qin, Ethan C. Chau, Zhuo Feng, Ahmed Awadallah, Jennifer Neville, Nikhil Rao |
| 2024 | ACL | S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs. | Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan, Jennifer Neville, Longqi Yang, Reid Andersen, Georg Buscher, Tara Safavi |
| 2024 | ACL | Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models. | Ying-Chun Lin, Jennifer Neville, Jack W. Stokes, Longqi Yang, Tara Safavi, Mengting Wan, Scott Counts, Siddharth Suri, Reid Andersen, Xiaofeng Xu, Deepak Gupta, Sujay Kumar Jauhar, Xia Song, Georg Buscher, Saurabh Tiwary, Brent J. Hecht, Jaime Teevan |
| 2024 | EMNLP | Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. | Tobias Schnabel, Jennifer Neville |
| 2024 | KDD | TnT-LLM: Text Mining at Scale with Large Language Models. | Mengting Wan, Tara Safavi, Sujay Kumar Jauhar, Yujin Kim, Scott Counts, Jennifer Neville, Siddharth Suri, Chirag Shah, Ryen W. White, Longqi Yang, Reid Andersen, Georg Buscher, Dhruv Joshi, Nagu Rangan |
| 2024 | NAACL | Automatic Pair Construction for Contrastive Post-training. | Canwen Xu, Corby Rosset, Ethan C. Chau, Luciano Del Corro, Shweti Mahajan, Julian J. McAuley, Jennifer Neville, Ahmed Awadallah, Nikhil Rao |
| 2024 | WWW | MS MARCO Web Search: A Large-scale Information-rich Web Dataset with Millions of Real Click Labels. | Qi Chen, Xiubo Geng, Corby Rosset, Carolyn Buractaon, Jingwen Lu, Tao Shen, Kun Zhou, Chenyan Xiong, Yeyun Gong, Paul N. Bennett, Nick Craswell, Xing Xie, Fan Yang, Bryan Tower, Nikhil Rao, Anlei Dong, Wenqi Jiang, Zheng Liu, Mingqin Li, Chuanjie Liu, Zengzhong Li, Rangan Majumder, Jennifer Neville, Andy Oakley, Knut Magne Risvik, Harsha Vardhan Simhadri, Manik Varma, Yujing Wang, Linjun Yang, Mao Yang, Ce Zhang |
| 2024 | UAI | On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBots. | Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan |
| 2023 | CIKM | DYANE: DYnamic Attributed Node rolEs Generative Model. | Giselle Zeno, Jennifer Neville |
| 2023 | ICML | Hindsight Learning for MDPs with Exogenous Inputs. | Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo de Oliveira Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan |
| 2023 | KDD | Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem. | Jiayi Liu, Jennifer Neville |
| 2023 | KDD | Workplace Recommendation with Temporal Network Objectives. | Kiran Tomlinson, Jennifer Neville, Longqi Yang, Mengting Wan, Cao Lu |
| 2023 | WWW | Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs. | Susheel Suresh, Mayank Shrivastava, Arko Mukherjee, Jennifer Neville, Pan Li |
| 2021 | ICML | A Collective Learning Framework to Boost GNN Expressiveness for Node Classification. | Mengyue Hang, Jennifer Neville, Bruno Ribeiro |
| 2021 | KDD | Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. | Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma |
| 2021 | WWW | DYMOND: DYnamic MOtif-NoDes Network Generative Model. | Giselle Zeno, Timothy La Fond, Jennifer Neville |
| 2020 | CIKM | MERL: Multi-View Edge Representation Learning in Social Networks. | Yi-Yu Lai, Jennifer Neville |
| 2020 | ECIR | ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis. | Changping Meng, Muhao Chen, Jie Mao, Jennifer Neville |
| 2020 | ICDM | Online Bayesian Sparse Learning with Spike and Slab Priors. | Shikai Fang, Shandian Zhe, Kuang-chih Lee, Kai Zhang, Jennifer Neville |
| 2020 | ICDM | A Hybrid Model for Learning Embeddings and Logical Rules Simultaneously from Knowledge Graphs. | Susheel Suresh, Jennifer Neville |
| 2020 | PAKDD | Role Equivalence Attention for Label Propagation in Graph Neural Networks. | Hogun Park, Jennifer Neville |
| 2020 | WWW | Dynamic Network Modeling from Motif-Activity. | Giselle Zeno, Timothy La Fond, Jennifer Neville |
| 2019 | AAAI | TransConv: Relationship Embedding in Social Networks. | Yi-Yu Lai, Jennifer Neville, Dan Goldwasser |
| 2019 | AISTATS | A Stein-Papangelou Goodness-of-Fit Test for Point Processes. | Jiasen Yang, Vinayak A. Rao, Jennifer Neville |
| 2019 | IJCAI | Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks. | Hogun Park, Jennifer Neville |
| 2019 | KDD | HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings. | Changping Meng, Jiasen Yang, Bruno Ribeiro, Jennifer Neville |
| 2019 | UAI | Social Reinforcement Learning to Combat Fake News Spread. | Mahak Goindani, Jennifer Neville |
| 2018 | AAAI | Subgraph Pattern Neural Networks for High-Order Graph Evolution Prediction. | Changping Meng, S. Chandra Mouli, Bruno Ribeiro, Jennifer Neville |
| 2018 | AISTATS | Nested CRP with Hawkes-Gaussian Processes. | Xi Tan, Vinayak A. Rao, Jennifer Neville |
| 2018 | ICDM | Multi-level Hypothesis Testing for Populations of Heterogeneous Networks. | Guilherme Gomes, Vinayak A. Rao, Jennifer Neville |
| 2018 | ICML | Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy. | Jiasen Yang, Qiang Liu, Vinayak A. Rao, Jennifer Neville |
| 2018 | KDD | Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction. | Mengyue Hang, Ian Pytlarz, Jennifer Neville |
| 2018 | KDD | Societal Impact of Data Science and Artificial Intelligence. | Foster J. Provost, James Hodson, Jeannette M. Wing, Qiang Yang, Jennifer Neville |
| 2018 | UAI | The Indian Buffet Hawkes Process to Model Evolving Latent Influences. | Xi Tan, Vinayak A. Rao, Jennifer Neville |
| 2017 | AAAI | Deep Collective Inference. | John Moore, Jennifer Neville |
| 2017 | IJCAI | Unified Representation and Lifted Sampling for Generative Models of Social Networks. | Pablo Robles-Granda, Sebastin Moreno, Jennifer Neville |
| 2017 | ICTIR | How to Exploit Relationships to Improve Predictions. | Jennifer Neville |
| 2017 | ICWSM | Should We Be Confident in Peer Effects Estimated From Social Network Crawls? | Jiasen Yang, Bruno Ribeiro, Jennifer Neville |
| 2017 | UAI | Decoupling Homophily and Reciprocity with Latent Space Network Models. | Jiasen Yang, Vinayak A. Rao, Jennifer Neville |
| 2016 | KDD | Sampling of Attributed Networks from Hierarchical Generative Models. | Pablo Robles-Granda, Sebastin Moreno, Jennifer Neville |
| 2015 | AAAI | Incorporating Assortativity and Degree Dependence into Scalable Network Models. | Stephen Mussmann, John Moore, Joseph John Pfeiffer III, Jennifer Neville |
| 2015 | ICDM | Efficient Graphlet Counting for Large Networks. | Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, Nick G. Duffield |
| 2015 | ICDM | Analyzing the Transferability of Collective Inference Models Across Networks. | Ransen Niu, Sebastin Moreno, Jennifer Neville |
| 2015 | WWW | Overcoming Relational Learning Biases to Accurately Predict Preferences in Large Scale Networks. | Joseph J. Pfeiffer III, Jennifer Neville, Paul N. Bennett |
| 2014 | CIKM | Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference. | Joseph John Pfeiffer III, Jennifer Neville, Paul N. Bennett |
| 2014 | ICDM | A Scalable Method for Exact Sampling from Kronecker Family Models. | Sebastin Moreno, Joseph J. Pfeiffer III, Jennifer Neville, Sergey Kirshner |
| 2014 | ICDM | Composite Likelihood Data Augmentation for Within-Network Statistical Relational Learning. | Joseph J. Pfeiffer III, Jennifer Neville, Paul N. Bennett |
| 2014 | KDD | Graph sample and hold: a framework for big-graph analytics. | Nesreen K. Ahmed, Nick G. Duffield, Jennifer Neville, Ramana Rao Kompella |
| 2014 | KDD | Assortativity in Chung Lu Random Graph Models. | Stephen Mussmann, John Moore, Joseph J. Pfeiffer III, Jennifer Neville |
| 2014 | WWW | Attributed graph models: modeling network structure with correlated attributes. | Joseph J. Pfeiffer III, Sebastin Moreno, Timothy La Fond, Jennifer Neville, Brian Gallagher |
| 2013 | ICDM | Network Hypothesis Testing Using Mixed Kronecker Product Graph Models. | Sebastin Moreno, Jennifer Neville |
| 2013 | KDD | Learning mixed kronecker product graph models with simulated method of moments. | Sebastin Moreno, Jennifer Neville, Sergey Kirshner |
| 2013 | WSDM | Modeling dynamic behavior in large evolving graphs. | Ryan A. Rossi, Brian Gallagher, Jennifer Neville, Keith Henderson |
| 2013 | WSDM | Collective inference for network data with copula latent markov networks. | Rongjing Xiang, Jennifer Neville |
| 2012 | CIKM | An analysis of how ensembles of collective classifiers improve predictions in graphs. | Hoda Eldardiry, Jennifer Neville |
| 2012 | ICWSM | Network Sampling Designs for Relational Classification. | Nesreen K. Ahmed, Jennifer Neville, Ramana Rao Kompella |
| 2012 | KDD | Space-efficient sampling from social activity streams. | Nesreen K. Ahmed, Jennifer Neville, Ramana Rao Kompella |
| 2012 | NSDI | Structured Comparative Analysis of Systems Logs to Diagnose Performance Problems. | Karthik Nagaraj, Charles Killian, Jennifer Neville |
| 2012 | PAKDD | Time-Evolving Relational Classification and Ensemble Methods. | Ryan A. Rossi, Jennifer Neville |
| 2012 | WWW | Role-dynamics: fast mining of large dynamic networks. | Ryan A. Rossi, Brian Gallagher, Jennifer Neville, Keith Henderson |
| 2011 | AAAI | Across-Model Collective Ensemble Classification. | Hoda Eldardiry, Jennifer Neville |
| 2011 | ICDM | Understanding Propagation Error and Its Effect on Collective Classification. | Rongjing Xiang, Jennifer Neville |
| 2011 | ICML | Relational Active Learning for Joint Collective Classification Models. | Ankit Kuwadekar, Jennifer Neville |
| 2011 | ICWSM | Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure. | Joseph J. Pfeiffer III, Jennifer Neville |
| 2010 | ICDE | Ranking for data repairs. | Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Neville |
| 2010 | INFOCOM | Predicting Prefix Availability in the Internet. | Ravish Khosla, Sonia Fahmy, Y. Charlie Hu, Jennifer Neville |
| 2010 | KDD | Modeling the evolution of discussion topics and communication to improve relational classification. | Ryan A. Rossi, Jennifer Neville |
| 2010 | WWW | Randomization tests for distinguishing social influence and homophily effects. | Timothy La Fond, Jennifer Neville |
| 2010 | WWW | Modeling relationship strength in online social networks. | Rongjing Xiang, Jennifer Neville, Monica Rogati |
| 2010 | SIGMOD | ERACER: a database approach for statistical inference and data cleaning. | Chris Mayfield, Jennifer Neville, Sunil Prabhakar |
| 2010 | SIGMOD | GDR: a system for guided data repair. | Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Neville, Mourad Ouzzani |
| 2009 | ICDM | Evaluating Statistical Tests for Within-Network Classifiers of Relational Data. | Jennifer Neville, Brian Gallagher, Tina Eliassi-Rad |
| 2009 | ICWSM | Using Transactional Information to Predict Link Strength in Online Social Networks. | Indika Kahanda, Jennifer Neville |
| 2008 | ICDE | Database Support for Probabilistic Attributes and Tuples. | Sarvjeet Singh, Chris Mayfield, Rahul Shah, Sunil Prabhakar, Susanne E. Hambrusch, Jennifer Neville, Reynold Cheng |
| 2008 | ICDM | A Shrinkage Approach for Modeling Non-stationary Relational Autocorrelation. | Pelin Angin, Jennifer Neville |
| 2008 | ICDM | Temporal-Relational Classifiers for Prediction in Evolving Domains. | Umang Sharan, Jennifer Neville |
| 2008 | ICDM | Pseudolikelihood EM for Within-network Relational Learning. | Rongjing Xiang, Jennifer Neville |
| 2007 | ILP | Bias/Variance Analysis for Relational Domains. | Jennifer Neville, David D. Jensen |
| 2005 | AAAI | Structure Learning for Statistical Relational Models. | Jennifer Neville |
| 2005 | ICDM | Leveraging Relational Autocorrelation with Latent Group Models. | Jennifer Neville, David D. Jensen |
| 2005 | KDD | Using relational knowledge discovery to prevent securities fraud. | Jennifer Neville, zgr Simsek, David D. Jensen, John Komoroske, Kelly Palmer, Henry G. Goldberg |
| 2004 | ICDM | Dependency Networks for Relational Data. | Jennifer Neville, David D. Jensen |
| 2004 | KDD | Why collective inference improves relational classification. | David D. Jensen, Jennifer Neville, Brian Gallagher |
| 2003 | ICDM | Simple Estimators for Relational Bayesian Classifiers. | Jennifer Neville, David D. Jensen, Brian Gallagher |
| 2003 | ICML | Avoiding Bias when Aggregating Relational Data with Degree Disparity. | David D. Jensen, Jennifer Neville, Michael Hay |
| 2003 | KDD | Learning relational probability trees. | Jennifer Neville, David D. Jensen, Lisa Friedland, Michael Hay |
| 2002 | ICML | Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning. | David D. Jensen, Jennifer Neville |
| 2002 | ILP | Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners. | David D. Jensen, Jennifer Neville |