Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning. - David D. Jensen; Jennifer Neville (ICML, 2002)

Autocorrelation and Linkage Cause Bias in Evaluation of Relational Learners. - David D. Jensen; Jennifer Neville (ILP, 2002)

Simple Estimators for Relational Bayesian Classifiers. - Jennifer Neville; David D. Jensen; Brian Gallagher (ICDM, 2003)

Avoiding Bias when Aggregating Relational Data with Degree Disparity. - David D. Jensen; Jennifer Neville; Michael Hay (ICML, 2003)

Learning relational probability trees. - Jennifer Neville; David D. Jensen; Lisa Friedland; Michael Hay (KDD, 2003)

Exploiting relational structure to understand publication patterns in high-energy physics. - Amy McGovern; Lisa Friedland; Michael Hay; Brian Gallagher; Andrew S. Fast; Jennifer Neville; David D. Jensen (SIGKDD Explor., 2003)

Dependency Networks for Relational Data. - Jennifer Neville; David D. Jensen (ICDM, 2004)

Why collective inference improves relational classification. - David D. Jensen; Jennifer Neville; Brian Gallagher (KDD, 2004)

Structure Learning for Statistical Relational Models. - Jennifer Neville (AAAI, 2005)

Leveraging Relational Autocorrelation with Latent Group Models. - Jennifer Neville; David D. Jensen (ICDM, 2005)

Using relational knowledge discovery to prevent securities fraud. - Jennifer Neville; Özgür Simsek; David D. Jensen; John Komoroske; Kelly Palmer; Henry G. Goldberg (KDD, 2005)

Bias/Variance Analysis for Relational Domains. - Jennifer Neville; David D. Jensen (ILP, 2007)

Relational Dependency Networks. - Jennifer Neville; David D. Jensen (J. Mach. Learn. Res., 2007)

Database Support for Probabilistic Attributes and Tuples. - Sarvjeet Singh; Chris Mayfield; Rahul Shah 001; Sunil Prabhakar 001; Susanne E. Hambrusch; Jennifer Neville; Reynold Cheng (ICDE, 2008)

A Shrinkage Approach for Modeling Non-stationary Relational Autocorrelation. - Pelin Angin; Jennifer Neville (ICDM, 2008)

Temporal-Relational Classifiers for Prediction in Evolving Domains. - Umang Sharan; Jennifer Neville (ICDM, 2008)

Pseudolikelihood EM for Within-network Relational Learning. - Rongjing Xiang; Jennifer Neville (ICDM, 2008)

AI's 10 to Watch. - James A. Hendler; Philipp Cimiano; Dmitri A. Dolgov; Anat Levin; Peter Mika; Brian Milch; Louis-Philippe Morency; Boris Motik; Jennifer Neville; Erik B. Sudderth; Luis von Ahn (IEEE Intell. Syst., 2008)

A bias/variance decomposition for models using collective inference. - Jennifer Neville; David D. Jensen (Mach. Learn., 2008)

Evaluating Statistical Tests for Within-Network Classifiers of Relational Data. - Jennifer Neville; Brian Gallagher; Tina Eliassi-Rad (ICDM, 2009)

Using Transactional Information to Predict Link Strength in Online Social Networks. - Indika Kahanda; Jennifer Neville (ICWSM, 2009)

Tied Kronecker product graph models to capture variance in network populations. - Sebastián Moreno; Sergey Kirshner; Jennifer Neville; S. V. N. Vishwanathan (Allerton, 2010)

Ranking for data repairs. - Mohamed Yakout; Ahmed K. Elmagarmid; Jennifer Neville (ICDE Workshops, 2010)

Predicting Prefix Availability in the Internet. - Ravish Khosla; Sonia Fahmy; Y. Charlie Hu; Jennifer Neville (INFOCOM, 2010)

Modeling the evolution of discussion topics and communication to improve relational classification. - Ryan A. Rossi; Jennifer Neville (SOMA@KDD, 2010)

Time-based sampling of social network activity graphs. - Nesreen K. Ahmed; Fredrick J. Berchmans; Jennifer Neville; Ramana Rao Kompella (MLG@KDD, 2010)

Multi-network fusion for collective inference. - Hoda Eldardiry; Jennifer Neville (MLG@KDD, 2010)

ERACER: a database approach for statistical inference and data cleaning. - Chris Mayfield; Jennifer Neville; Sunil Prabhakar 001 (SIGMOD Conference, 2010)

GDR: a system for guided data repair. - Mohamed Yakout; Ahmed K. Elmagarmid; Jennifer Neville; Mourad Ouzzani (SIGMOD Conference, 2010)

Randomization tests for distinguishing social influence and homophily effects. - Timothy La Fond; Jennifer Neville (WWW, 2010)

Modeling relationship strength in online social networks. - Rongjing Xiang; Jennifer Neville; Monica Rogati (WWW, 2010)

Across-Model Collective Ensemble Classification. - Hoda Eldardiry; Jennifer Neville (AAAI, 2011)

Understanding Propagation Error and Its Effect on Collective Classification. - Rongjing Xiang; Jennifer Neville (ICDM, 2011)

Relational Active Learning for Joint Collective Classification Models. - Ankit Kuwadekar; Jennifer Neville (ICML, 2011)

Methods to Determine Node Centrality and Clustering in Graphs with Uncertain Structure. - Joseph J. Pfeiffer III; Jennifer Neville (ICWSM, 2011)

Correcting Bias in Statistical Tests for Network Classifier Evaluation. - Tao Wang; Jennifer Neville; Brian Gallagher; Tina Eliassi-Rad (ECML/PKDD (3), 2011)

Gender demographics trends and changes in U.S. CS departments. - Douglas Baumann; Susanne E. Hambrusch; Jennifer Neville (Commun. ACM, 2011)

Prediction models for long-term Internet prefix availability. - Ravish Khosla; Sonia Fahmy; Y. Charlie Hu; Jennifer Neville (Comput. Networks, 2011)

Representations and Ensemble Methods for Dynamic Relational Classification - Ryan A. Rossi; Jennifer Neville (CoRR, 2011)

Relational Learning with One Network: An Asymptotic Analysis. - Rongjing Xiang; Jennifer Neville (AISTATS, 2011)

Introduction to the special issue on mining and learning with graphs. - S. V. N. Vishwanathan; Samuel Kaski; Jennifer Neville; Stefan Wrobel (Mach. Learn., 2011)

Guided data repair. - Mohamed Yakout; Ahmed K. Elmagarmid; Jennifer Neville; Mourad Ouzzani; Ihab F. Ilyas (Proc. VLDB Endow., 2011)

An analysis of how ensembles of collective classifiers improve predictions in graphs. - Hoda Eldardiry; Jennifer Neville (CIKM, 2012)

Network Sampling Designs for Relational Classification. - Nesreen K. Ahmed; Jennifer Neville; Ramana Rao Kompella (ICWSM, 2012)

Space-efficient sampling from social activity streams. - Nesreen K. Ahmed; Jennifer Neville; Ramana Rao Kompella (BigMine, 2012)

Structured Comparative Analysis of Systems Logs to Diagnose Performance Problems. - Karthik Nagaraj; Charles Killian; Jennifer Neville (NSDI, 2012)

Time-Evolving Relational Classification and Ensemble Methods. - Ryan A. Rossi; Jennifer Neville (PAKDD (1), 2012)

The Impact of Communication Structure and Interpersonal Dependencies on Distributed Teams. - Timothy La Fond; Dan Roberts; Jennifer Neville; James Tyler; Stacey L. Connaughton (SocialCom/PASSAT, 2012)

Fast Generation of Large Scale Social Networks While Incorporating Transitive Closures. - Joseph J. Pfeiffer III; Timothy La Fond; Sebastián Moreno; Jennifer Neville (SocialCom/PASSAT, 2012)

Role-dynamics: fast mining of large dynamic networks. - Ryan A. Rossi; Brian Gallagher; Jennifer Neville; Keith Henderson (WWW (Companion Volume), 2012)

Fast Generation of Large Scale Social Networks with Clustering - Joseph J. Pfeiffer III; Timothy La Fond; Sebastián Moreno; Jennifer Neville (CoRR, 2012)

Transforming Graph Representations for Statistical Relational Learning - Ryan A. Rossi; Luke K. McDowell; David W. Aha; Jennifer Neville (CoRR, 2012)

Dynamic Behavioral Mixed-Membership Model for Large Evolving Networks - Ryan A. Rossi; Brian Gallagher; Jennifer Neville; Keith Henderson (CoRR, 2012)

Transforming Graph Data for Statistical Relational Learning. - Ryan A. Rossi; Luke K. McDowell; David William Aha; Jennifer Neville (J. Artif. Intell. Res., 2012)

Correcting evaluation bias of relational classifiers with network cross validation. - Jennifer Neville; Brian Gallagher; Tina Eliassi-Rad; Tao Wang (Knowl. Inf. Syst., 2012)

Network Hypothesis Testing Using Mixed Kronecker Product Graph Models. - Sebastián Moreno; Jennifer Neville (ICDM, 2013)

Learning mixed kronecker product graph models with simulated method of moments. - Sebastián Moreno; Jennifer Neville; Sergey Kirshner (KDD, 2013)

Modeling dynamic behavior in large evolving graphs. - Ryan A. Rossi; Brian Gallagher; Jennifer Neville; Keith Henderson (WSDM, 2013)

Collective inference for network data with copula latent markov networks. - Rongjing Xiang; Jennifer Neville (WSDM, 2013)

LBSN 2012 workshop report: the Fifth ACM SIGSPATIAL International Workshop on Location-Based Social Networks (Redondo Beach, California - November 6, 2012). - Gabriel Ghinita; Jennifer Neville; Shawn D. Newsam (ACM SIGSPATIAL Special, 2013)

Network Sampling: From Static to Streaming Graphs. - Nesreen K. Ahmed; Jennifer Neville; Ramana Rao Kompella (ACM Trans. Knowl. Discov. Data, 2013)

Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference. - Joseph John Pfeiffer III; Jennifer Neville; Paul N. Bennett (CIKM, 2014)

A Scalable Method for Exact Sampling from Kronecker Family Models. - Sebastián Moreno; Joseph J. Pfeiffer III; Jennifer Neville; Sergey Kirshner (ICDM, 2014)

Composite Likelihood Data Augmentation for Within-Network Statistical Relational Learning. - Joseph J. Pfeiffer III; Jennifer Neville; Paul N. Bennett (ICDM, 2014)

Graph sample and hold: a framework for big-graph analytics. - Nesreen K. Ahmed; Nick G. Duffield; Jennifer Neville; Ramana Rao Kompella (KDD, 2014)

Assortativity in Chung Lu Random Graph Models. - Stephen Mussmann; John Moore; Joseph J. Pfeiffer III; Jennifer Neville (SNAKDD, 2014)

Attributed graph models: modeling network structure with correlated attributes. - Joseph J. Pfeiffer III; Sebastián Moreno; Timothy La Fond; Jennifer Neville; Brian Gallagher (WWW, 2014)

Learning the Latent State Space of Time-Varying Graphs. - Nesreen K. Ahmed; Christopher Cole; Jennifer Neville (CoRR, 2014)

Anomaly Detection in Dynamic Networks of Varying Size. - Timothy La Fond; Jennifer Neville; Brian Gallagher (CoRR, 2014)

Signal Processing for Big Data [From the Guest Editors]. - Georgios B. Giannakis; Francis R. Bach; Raphael Cendrillon; Michael W. Mahoney; Jennifer Neville (IEEE Signal Process. Mag., 2014)

Incorporating Assortativity and Degree Dependence into Scalable Network Models. - Stephen Mussmann; John Moore; Joseph John Pfeiffer III; Jennifer Neville (AAAI, 2015)

Efficient Graphlet Counting for Large Networks. - Nesreen K. Ahmed; Jennifer Neville; Ryan A. Rossi; Nick G. Duffield (ICDM, 2015)

Analyzing the Transferability of Collective Inference Models Across Networks. - Ransen Niu; Sebastián Moreno; Jennifer Neville (ICDM Workshops, 2015)

Overcoming Relational Learning Biases to Accurately Predict Preferences in Large Scale Networks. - Joseph J. Pfeiffer III; Jennifer Neville; Paul N. Bennett (WWW, 2015)

Fast Parallel Graphlet Counting for Large Networks. - Nesreen K. Ahmed; Jennifer Neville; Ryan A. Rossi; Nick G. Duffield (CoRR, 2015)

Using Bayesian Network Representations for Effective Sampling from Generative Network Models. - Pablo Robles-Granda; Sebastián Moreno; Jennifer Neville (CoRR, 2015)

Sampling of Attributed Networks from Hierarchical Generative Models. - Pablo Robles-Granda; Sebastián Moreno; Jennifer Neville (KDD, 2016)

Better Together: Combining Language and Social Interactions into a Shared Representation. - Yi-Yu Lai; Chang Li 005; Dan Goldwasser; Jennifer Neville (TextGraphs@NAACL-HLT, 2016)

Combining Gradient Boosting Machines with Collective Inference to Predict Continuous Values. - Iman Al-Odah; Jennifer Neville (CoRR, 2016)

Size-Consistent Statistics for Anomaly Detection in Dynamic Networks. - Timothy La Fond; Jennifer Neville; Brian Gallagher (CoRR, 2016)

Deep Collective Inference. - John Moore; Jennifer Neville (AAAI, 2017)

How to Exploit Relationships to Improve Predictions. - Jennifer Neville (ICTIR, 2017)

Should We Be Confident in Peer Effects Estimated From Social Network Crawls? - Jiasen Yang; Bruno Ribeiro 001; Jennifer Neville (ICWSM, 2017)

Unified Representation and Lifted Sampling for Generative Models of Social Networks. - Pablo Robles-Granda; Sebastián Moreno; Jennifer Neville (IJCAI, 2017)

Decoupling Homophily and Reciprocity with Latent Space Network Models. - Jiasen Yang; Vinayak A. Rao; Jennifer Neville (UAI, 2017)

Identifying User Survival Types via Clustering of Censored Social Network Data. - S. Chandra Mouli; Abhishek Naik; Bruno Ribeiro 001; Jennifer Neville (CoRR, 2017)

Stochastic Gradient Descent for Relational Logistic Regression via Partial Network Crawls. - Jiasen Yang; Bruno Ribeiro 001; Jennifer Neville (CoRR, 2017)

Graphlet decomposition: framework, algorithms, and applications. - Nesreen K. Ahmed; Jennifer Neville; Ryan A. Rossi; Nick G. Duffield; Theodore L. Willke (Knowl. Inf. Syst., 2017)

Subgraph Pattern Neural Networks for High-Order Graph Evolution Prediction. - Changping Meng; S. Chandra Mouli; Bruno Ribeiro 001; Jennifer Neville (AAAI, 2018)

Nested CRP with Hawkes-Gaussian Processes. - Xi Tan; Vinayak A. Rao; Jennifer Neville (AISTATS, 2018)

Multi-level Hypothesis Testing for Populations of Heterogeneous Networks. - Guilherme Gomes; Vinayak A. Rao; Jennifer Neville (ICDM, 2018)

Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy. - Jiasen Yang; Qiang Liu; Vinayak A. Rao; Jennifer Neville (ICML, 2018)

Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction. - Mengyue Hang; Ian Pytlarz; Jennifer Neville (KDD, 2018)

Societal Impact of Data Science and Artificial Intelligence. - Foster J. Provost; James Hodson; Jeannette M. Wing; Qiang Yang 001; Jennifer Neville (KDD, 2018)

The Indian Buffet Hawkes Process to Model Evolving Latent Influences. - Xi Tan; Vinayak A. Rao; Jennifer Neville (UAI, 2018)

Scalable and exact sampling method for probabilistic generative graph models. - Sebastián Moreno; Joseph J. Pfeiffer III; Jennifer Neville (Data Min. Knowl. Discov., 2018)

Meta-Programming for Statistical Machine Learning (NII Shonan Meeting 2018-7). - Oleg Kiselyov; Tiark Rompf; Jennifer Neville; Yukiyoshi Kameyama (NII Shonan Meet. Rep., 2018)

Designing Size Consistent Statistics for Accurate Anomaly Detection in Dynamic Networks. - Timothy La Fond; Jennifer Neville; Brian Gallagher (ACM Trans. Knowl. Discov. Data, 2018)

Tied Kronecker Product Graph Models to Capture Variance in Network Populations. - Sebastián Moreno; Jennifer Neville; Sergey Kirshner (ACM Trans. Knowl. Discov. Data, 2018)

TransConv: Relationship Embedding in Social Networks. - Yi-Yu Lai; Jennifer Neville; Dan Goldwasser (AAAI, 2019)

A Stein-Papangelou Goodness-of-Fit Test for Point Processes. - Jiasen Yang; Vinayak A. Rao; Jennifer Neville (AISTATS, 2019)

Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks. - Hogun Park; Jennifer Neville (IJCAI, 2019)

HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings. - Changping Meng; Jiasen Yang; Bruno Ribeiro 001; Jennifer Neville (KDD, 2019)

Social Reinforcement Learning to Combat Fake News Spread. - Mahak Goindani; Jennifer Neville (UAI, 2019)

Community detection over a heterogeneous population of non-aligned networks. - Guilherme Gomes; Vinayak A. Rao; Jennifer Neville (CoRR, 2019)

Deep Lifetime Clustering. - S. Chandra Mouli; Leonardo Teixeira; Jennifer Neville; Bruno Ribeiro 001 (CoRR, 2019)

Variational Random Function Model for Network Modeling. - Zenglin Xu; Bin Liu 022; Shandian Zhe; Haoli Bai; Zihan Wang 002; Jennifer Neville (IEEE Trans. Neural Networks Learn. Syst., 2019)

Cluster-Based Social Reinforcement Learning. - Mahak Goindani; Jennifer Neville (AAMAS, 2020)

MERL: Multi-View Edge Representation Learning in Social Networks. - Yi-Yu Lai; Jennifer Neville (CIKM, 2020)

ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis. - Changping Meng; Muhao Chen 001; Jie Mao; Jennifer Neville (ECIR (1), 2020)

Online Bayesian Sparse Learning with Spike and Slab Priors. - Shikai Fang; Shandian Zhe; Kuang-chih Lee; Kai Zhang 001; Jennifer Neville (ICDM, 2020)

A Hybrid Model for Learning Embeddings and Logical Rules Simultaneously from Knowledge Graphs. - Susheel Suresh; Jennifer Neville (ICDM, 2020)

Role Equivalence Attention for Label Propagation in Graph Neural Networks. - Hogun Park; Jennifer Neville (PAKDD (2), 2020)

Dynamic Network Modeling from Motif-Activity. - Giselle Zeno; Timothy La Fond; Jennifer Neville (WWW (Companion Volume), 2020)

A Collective Learning Framework to Boost GNN Expressiveness. - Mengyue Hang; Jennifer Neville; Bruno Ribeiro 001 (CoRR, 2020)

Ensemble Learning for Relational Data. - Hoda Eldardiry; Jennifer Neville; Ryan A. Rossi (J. Mach. Learn. Res., 2020)

Towards Decentralized Social Reinforcement Learning via Ego-Network Extrapolation. - Mahak Goindani; Jennifer Neville (AAMAS, 2021)

A Collective Learning Framework to Boost GNN Expressiveness for Node Classification. - Mengyue Hang; Jennifer Neville; Bruno Ribeiro 001 (ICML, 2021)

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 005; Jianzhu Ma (KDD, 2021)

Adversarial Graph Augmentation to Improve Graph Contrastive Learning. - Susheel Suresh; Pan Li 005; Cong Hao; Jennifer Neville (NeurIPS, 2021)

DYMOND: DYnamic MOtif-NoDes Network Generative Model. - Giselle Zeno; Timothy La Fond; Jennifer Neville (WWW, 2021)

Lightweight Compositional Embeddings for Incremental Streaming Recommendation. - Mengyue Hang; Tobias Schnabel; Longqi Yang; Jennifer Neville (CoRR, 2022)

Federated Graph Representation Learning using Self-Supervision. - Susheel Suresh; Danny Godbout; Arko Mukherjee; Mayank Shrivastava; Jennifer Neville; Pan Li 005 (CoRR, 2022)

DYANE: DYnamic Attributed Node rolEs Generative Model. - Giselle Zeno; Jennifer Neville (CIKM, 2023)

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 (ICML, 2023)

Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem. - Jiayi Liu 005; Jennifer Neville (KDD, 2023)

Workplace Recommendation with Temporal Network Objectives. - Kiran Tomlinson; Jennifer Neville; Longqi Yang; Mengting Wan; Cao Lu (KDD, 2023)

Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs. - Susheel Suresh; Mayank Shrivastava; Arko Mukherjee; Jennifer Neville; Pan Li 005 (WWW, 2023)

Creating generalizable downstream graph models with random projections. - Anton Amirov; Chris Quirk; Jennifer Neville (CoRR, 2023)

Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with Bridgeness. - Hogun Park; Jennifer Neville (CoRR, 2023)

Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies. - Chirag Shah 001; Ryen W. White; Reid Andersen; Georg Buscher; Scott Counts; Sarkar Snigdha Sarathi Das; Ali Montazer; Sathish Manivannan; Jennifer Neville; Xiaochuan Ni 001; Nagu Rangan; Tara Safavi; et al. (CoRR, 2023)

Contrastive Post-training Large Language Models on Data Curriculum. - Canwen Xu; Corby Rosset; Luciano Del Corro; Shweti Mahajan; Julian J. McAuley; Jennifer Neville; Ahmed Hassan Awadallah; Nikhil Rao 001 (CoRR, 2023)

PEARL: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers. - Sheshera Mysore; Zhuoran Lu; Mengting Wan; Longqi Yang; Steve Menezes; Tina Baghaee; Emmanuel Barajas Gonzalez; Jennifer Neville; Tara Safavi (CoRR, 2023)

Generating post-hoc explanations for Skip-gram-based node embeddings by identifying important nodes with bridgeness. - Hogun Park; Jennifer Neville (Neural Networks, 2023)

S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs. - Sarkar Snigdha Sarathi Das; Chirag Shah 001; Mengting Wan; Jennifer Neville; Longqi Yang; Reid Andersen; Georg Buscher; Tara Safavi (ACL (Findings), 2024)

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; et al. (ACL (1), 2024)

Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. - Tobias Schnabel; Jennifer Neville (EMNLP (Findings), 2024)

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 001; Ryen W. White; Longqi Yang; Reid Andersen; Georg Buscher; et al. (KDD, 2024)

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 001; Nikhil Rao 001 (NAACL-HLT (Findings), 2024)

On Overcoming Miscalibrated Conversational Priors in LLM-based ChatBots. - Christine Herlihy; Jennifer Neville; Tobias Schnabel; Adith Swaminathan (UAI, 2024)

MS MARCO Web Search: A Large-scale Information-rich Web Dataset with Millions of Real Click Labels. - Qi Chen 009; Xiubo Geng; Corby Rosset; Carolyn Buractaon; Jingwen Lu; Tao Shen 001; Kun Zhou 002; Chenyan Xiong; Yeyun Gong; Paul N. Bennett; Nick Craswell; Xing Xie 001; et al. (WWW (Companion Volume), 2024)

CliqueParcel: An Approach For Batching LLM Prompts That Jointly Optimizes Efficiency And Faithfulness. - Jiayi Liu 005; Tinghan Yang; Jennifer Neville (CoRR, 2024)

Researchy Questions: A Dataset of Multi-Perspective, Decompositional Questions for LLM Web Agents. - Corby Rosset; Ho-Lam Chung; Guanghui Qin; Ethan C. Chau; Zhuo Feng; Ahmed Awadallah 001; Jennifer Neville; Nikhil Rao 001 (CoRR, 2024)

Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. - Tobias Schnabel; Jennifer Neville (CoRR, 2024)

The Use of Generative Search Engines for Knowledge Work and Complex Tasks. - Siddharth Suri; Scott Counts; Leijie Wang; Chacha Chen; Mengting Wan; Tara Safavi; Jennifer Neville; Chirag Shah 001; Ryen W. White; Reid Andersen; Georg Buscher; Sathish Manivannan; et al. (CoRR, 2024)

Corporate Communication Companion (CCC): An LLM-empowered Writing Assistant for Workplace Social Media. - Zhuoran Lu; Sheshera Mysore; Tara Safavi; Jennifer Neville; Longqi Yang; Mengting Wan (CoRR, 2024)

LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation. - Jiaxing Zhang 002; Jiayi Liu 005; Dongsheng Luo; Jennifer Neville; Hua Wei 001 (CoRR, 2024)

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; Xiaofeng Xu; Xia Song; Jennifer Neville (CoRR, 2024)

Improving Node Representation by Boosting Target-Aware Contrastive Loss. - Ying-Chun Lin; Jennifer Neville (CoRR, 2024)

Rethinking Node Representation Interpretation through Relation Coherence. - Ying-Chun Lin; Jennifer Neville; Cassiano Becker; Purvanshi Metha; Nabiha Asghar; Vipul Agarwal (CoRR, 2024)

GenTool: Enhancing Tool Generalization in Language Models through Zero-to-One and Weak-to-Strong Simulation. - Jie He 004; Jennifer Neville; Mengting Wan; Longqi Yang; Hui Liu; Xiaofeng Xu; Xia Song; Jeff Z. Pan; Pei Zhou (ACL (Findings), 2025)

Node Similarities under Random Projections: Limits and Pathological Cases. - Tvrtko Tadic; Cassiano O. Becker; Jennifer Neville (ICLR, 2025)

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 001; Jennifer Neville; Nikhil Rao 001 (SIGIR, 2025)

Group Preference Alignment: Customized LLM Response Generation from In-Situ Conversations. - Ishani Mondal; Jack W. Stokes; Sujay Kumar Jauhar; Longqi Yang; Mengting Wan; Xiaofeng Xu; Xia Song; Jennifer Neville (CoRR, 2025)

LLMs Get Lost In Multi-Turn Conversation. - Philippe Laban; Hiroaki Hayashi; Yingbo Zhou; Jennifer Neville (CoRR, 2025)

Lost in Transmission: When and Why LLMs Fail to Reason Globally. - Tobias Schnabel; Kiran Tomlinson; Adith Swaminathan; Jennifer Neville (CoRR, 2025)

Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies. - Chirag Shah 001; Ryen White; Reid Andersen; Georg Buscher; Scott Counts; Sarkar Snigdha Sarathi Das; Ali Montazer; Sathish Manivannan; Jennifer Neville; Nagu Rangan; Tara Safavi; Siddharth Suri; et al. (ACM Trans. Web, 2025)