Jennifer Neville

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 89

Top Venues

Publications

Zhuoran Lu, Sheshera Mysore, Tara Safavi, Jennifer Neville, Longqi Yang, Mengting Wan
Corporate Communication Companion (CCC): An LLM-empowered Writing Assistant for Workplace Social Media. CoRR (2024)
Tvrtko Tadic, Cassiano Becker, Jennifer Neville
Node Similarities under Random Projections: Limits and Pathological Cases. CoRR (2024)
Corby Rosset, Ho-Lam Chung, Guanghui Qin, Ethan C. Chau, Zhuo Feng, Ahmed Awadallah, Jennifer Neville, Nikhil Rao
Researchy Questions: A Dataset of Multi-Perspective, Decompositional Questions for LLM Web Agents. CoRR (2024)
Jiayi Liu, Tinghan Yang, Jennifer Neville
CliqueParcel: An Approach For Batching LLM Prompts That Jointly Optimizes Efficiency And Faithfulness. CoRR (2024)
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
MS MARCO Web Search: A Large-scale Information-rich Web Dataset with Millions of Real Click Labels. WWW (Companion Volume) (2024)
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
Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models. CoRR (2024)
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
TnT-LLM: Text Mining at Scale with Large Language Models. KDD (2024)
Siddharth Suri, Scott Counts, Leijie Wang, Chacha Chen, Mengting Wan, Tara Safavi, Jennifer Neville, Chirag Shah, Ryen W. White, Reid Andersen, Georg Buscher, Sathish Manivannan, Nagu Rangan, Longqi Yang
The Use of Generative Search Engines for Knowledge Work and Complex Tasks. CoRR (2024)
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
Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models. ACL (1) (2024)
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
MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels. CoRR (2024)
Tobias Schnabel, Jennifer Neville
Prompts As Programs: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization. CoRR (2024)
Jiaxing Zhang, Jiayi Liu, Dongsheng Luo, Jennifer Neville, Hua Wei
LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation. CoRR (2024)
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
TnT-LLM: Text Mining at Scale with Large Language Models. CoRR (2024)
Christine Herlihy, Jennifer Neville, Tobias Schnabel, Adith Swaminathan
On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbots. CoRR (2024)
Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan, Jennifer Neville, Longqi Yang, Reid Andersen, Georg Buscher, Tara Safavi
S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs. ACL (Findings) (2024)
Hogun Park, Jennifer Neville
. Neural Networks 164 (2023)
Chirag Shah, Ryen W. White, Reid Andersen, Georg Buscher, Scott Counts, Sarkar Snigdha Sarathi Das, Ali Montazer, Sathish Manivannan, Jennifer Neville, Xiaochuan Ni, Nagu Rangan, Tara Safavi, Siddharth Suri, Mengting Wan, Leijie Wang, Longqi Yang
Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies. CoRR (2023)
Kiran Tomlinson, Jennifer Neville, Longqi Yang, Mengting Wan, Cao Lu
Workplace Recommendation with Temporal Network Objectives. KDD (2023)
Susheel Suresh, Mayank Shrivastava, Arko Mukherjee, Jennifer Neville, Pan Li
Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs. WWW (2023)
Hogun Park, Jennifer Neville
Generating Post-hoc Explanations for Skip-gram-based Node Embeddings by Identifying Important Nodes with Bridgeness. CoRR (2023)
Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, Steve Menezes, Tina Baghaee, Emmanuel Barajas Gonzalez, Jennifer Neville, Tara Safavi
PEARL: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers. CoRR (2023)
Giselle Zeno, Jennifer Neville
DYANE: DYnamic Attributed Node rolEs Generative Model. CIKM (2023)
Jiayi Liu, Jennifer Neville
Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem. CoRR (2023)
Sean R. Sinclair, Felipe Vieira Frujeri, Ching-An Cheng, Luke Marshall, Hugo De Oliveira Barbalho, Jingling Li, Jennifer Neville, Ishai Menache, Adith Swaminathan
Hindsight Learning for MDPs with Exogenous Inputs. ICML (2023)
Anton Amirov, Chris Quirk, Jennifer Neville
Creating generalizable downstream graph models with random projections. CoRR (2023)
Jiayi Liu, Jennifer Neville
Stationary Algorithmic Balancing For Dynamic Email Re-Ranking Problem. KDD (2023)
Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan, Jennifer Neville, Longqi Yang, Reid Andersen, Georg Buscher, Tara Safavi
S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs. CoRR (2023)
Canwen Xu, Corby Rosset, Luciano Del Corro, Shweti Mahajan, Julian J. McAuley, Jennifer Neville, Ahmed Hassan Awadallah, Nikhil Rao
Contrastive Post-training Large Language Models on Data Curriculum. CoRR (2023)
Giselle Zeno, Timothy La Fond, Jennifer Neville
DYMOND: DYnamic MOtif-NoDes Network Generative Model. CoRR (2023)
Mengyue Hang, Tobias Schnabel, Longqi Yang, Jennifer Neville
Lightweight Compositional Embeddings for Incremental Streaming Recommendation. CoRR (2022)
Susheel Suresh, Danny Godbout, Arko Mukherjee, Mayank Shrivastava, Jennifer Neville, Pan Li
Federated Graph Representation Learning using Self-Supervision. CoRR (2022)
Mengyue Hang, Jennifer Neville, Bruno Ribeiro
A Collective Learning Framework to Boost GNN Expressiveness for Node Classification. ICML (2021)
Changping Meng, Muhao Chen, Jie Mao, Jennifer Neville
ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis. CoRR (2021)
Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville
Adversarial Graph Augmentation to Improve Graph Contrastive Learning. CoRR (2021)
Giselle Zeno, Timothy La Fond, Jennifer Neville
DYMOND: DYnamic MOtif-NoDes Network Generative Model. WWW (2021)
Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. CoRR (2021)
Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville
Adversarial Graph Augmentation to Improve Graph Contrastive Learning. NeurIPS (2021)
Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. KDD (2021)
Mahak Goindani, Jennifer Neville
Towards Decentralized Social Reinforcement Learning via Ego-Network Extrapolation. AAMAS (2021)
Yi-Yu Lai, Jennifer Neville
MERL: Multi-View Edge Representation Learning in Social Networks. CIKM (2020)
Giselle Zeno, Timothy La Fond, Jennifer Neville
Dynamic Network Modeling from Motif-Activity. WWW (Companion Volume) (2020)
Mahak Goindani, Jennifer Neville
Cluster-Based Social Reinforcement Learning. CoRR (2020)
Hogun Park, Jennifer Neville
Role Equivalence Attention for Label Propagation in Graph Neural Networks. PAKDD (2) (2020)
Mengyue Hang, Jennifer Neville, Bruno Ribeiro
A Collective Learning Framework to Boost GNN Expressiveness. CoRR (2020)
Shikai Fang, Shandian Zhe, Kuang-chih Lee, Kai Zhang, Jennifer Neville
Online Bayesian Sparse Learning with Spike and Slab Priors. ICDM (2020)
Susheel Suresh, Jennifer Neville
A Hybrid Model for Learning Embeddings and Logical Rules Simultaneously from Knowledge Graphs. ICDM (2020)
Mahak Goindani, Jennifer Neville
Cluster-Based Social Reinforcement Learning. AAMAS (2020)
Changping Meng, Muhao Chen, Jie Mao, Jennifer Neville
ReadNet: A Hierarchical Transformer Framework for Web Article Readability Analysis. ECIR (1) (2020)
Hoda Eldardiry, Jennifer Neville, Ryan A. Rossi
Ensemble Learning for Relational Data. J. Mach. Learn. Res. 21 (2020)
Susheel Suresh, Jennifer Neville
A Hybrid Model for Learning Embeddings and Logical Rules Simultaneously from Knowledge Graphs. CoRR (2020)
Hogun Park, Jennifer Neville
Exploiting Interaction Links for Node Classification with Deep Graph Neural Networks. IJCAI (2019)
Guilherme Gomes, Vinayak A. Rao, Jennifer Neville
Community detection over a heterogeneous population of non-aligned networks. CoRR (2019)
Jiasen Yang, Vinayak A. Rao, Jennifer Neville
A Stein-Papangelou Goodness-of-Fit Test for Point Processes. AISTATS (2019)
Mahak Goindani, Jennifer Neville
Social Reinforcement Learning to Combat Fake News Spread. UAI (2019)
Zenglin Xu, Bin Liu, Shandian Zhe, Haoli Bai, Zihan Wang, Jennifer Neville
Variational Random Function Model for Network Modeling. IEEE Trans. Neural Networks Learn. Syst. 30 (1) (2019)
Yi-Yu Lai, Jennifer Neville, Dan Goldwasser
TransConv: Relationship Embedding in Social Networks. AAAI (2019)
Changping Meng, Jiasen Yang, Bruno Ribeiro, Jennifer Neville
HATS: A Hierarchical Sequence-Attention Framework for Inductive Set-of-Sets Embeddings. KDD (2019)
S. Chandra Mouli, Leonardo Teixeira, Jennifer Neville, Bruno Ribeiro
Deep Lifetime Clustering. CoRR (2019)
Changping Meng, S. Chandra Mouli, Bruno Ribeiro, Jennifer Neville
Subgraph Pattern Neural Networks for High-Order Graph Evolution Prediction. AAAI (2018)
Sebastián Moreno, Jennifer Neville, Sergey Kirshner
Tied Kronecker Product Graph Models to Capture Variance in Network Populations. ACM Trans. Knowl. Discov. Data 12 (3) (2018)
Guilherme Gomes, Vinayak A. Rao, Jennifer Neville
Multi-level hypothesis testing for populations of heterogeneous networks. CoRR (2018)
Guilherme Gomes, Vinayak A. Rao, Jennifer Neville
Multi-level Hypothesis Testing for Populations of Heterogeneous Networks. ICDM (2018)
Timothy La Fond, Jennifer Neville, Brian Gallagher
Designing Size Consistent Statistics for Accurate Anomaly Detection in Dynamic Networks. ACM Trans. Knowl. Discov. Data 12 (4) (2018)
Foster J. Provost, James Hodson, Jeannette M. Wing, Qiang Yang, Jennifer Neville
Societal Impact of Data Science and Artificial Intelligence. KDD (2018)
Sebastián Moreno, Joseph J. Pfeiffer III, Jennifer Neville
Scalable and exact sampling method for probabilistic generative graph models. Data Min. Knowl. Discov. 32 (6) (2018)
Xi Tan, Vinayak A. Rao, Jennifer Neville
Nested CRP with Hawkes-Gaussian Processes. AISTATS (2018)
Xi Tan, Vinayak A. Rao, Jennifer Neville
The Indian Buffet Hawkes Process to Model Evolving Latent Influences. UAI (2018)
Mengyue Hang, Ian Pytlarz, Jennifer Neville
Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction. CoRR (2018)
Oleg Kiselyov, Tiark Rompf, Jennifer Neville, Yukiyoshi Kameyama
Meta-Programming for Statistical Machine Learning (NII Shonan Meeting 2018-7). NII Shonan Meet. Rep. 2018 (2018)
Jiasen Yang, Qiang Liu, Vinayak A. Rao, Jennifer Neville
Goodness-of-fit Testing for Discrete Distributions via Stein Discrepancy. ICML (2018)
Mengyue Hang, Ian Pytlarz, Jennifer Neville
Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction. KDD (2018)
John Moore, Jennifer Neville
Deep Collective Inference. AAAI (2017)
Pablo Robles-Granda, Sebastián Moreno, Jennifer Neville
Unified Representation and Lifted Sampling for Generative Models of Social Networks. IJCAI (2017)
Jennifer Neville
How to Exploit Relationships to Improve Predictions. ICTIR (2017)
Jiasen Yang, Bruno Ribeiro, Jennifer Neville
Should We Be Confident in Peer Effects Estimated From Social Network Crawls? ICWSM (2017)
S. Chandra Mouli, Abhishek Naik, Bruno Ribeiro, Jennifer Neville
Identifying User Survival Types via Clustering of Censored Social Network Data. CoRR (2017)
Jiasen Yang, Vinayak A. Rao, Jennifer Neville
Decoupling Homophily and Reciprocity with Latent Space Network Models. UAI (2017)
Jiasen Yang, Bruno Ribeiro, Jennifer Neville
Stochastic Gradient Descent for Relational Logistic Regression via Partial Network Crawls. CoRR (2017)
Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, Nick G. Duffield, Theodore L. Willke
Graphlet decomposition: framework, algorithms, and applications. Knowl. Inf. Syst. 50 (3) (2017)
Iman Al-Odah, Jennifer Neville
Combining Gradient Boosting Machines with Collective Inference to Predict Continuous Values. CoRR (2016)
Yi-Yu Lai, Chang Li, Dan Goldwasser, Jennifer Neville
Better Together: Combining Language and Social Interactions into a Shared Representation. TextGraphs@NAACL-HLT (2016)
Pablo Robles-Granda, Sebastián Moreno, Jennifer Neville
Sampling of Attributed Networks from Hierarchical Generative Models. KDD (2016)
Timothy La Fond, Jennifer Neville, Brian Gallagher
Size-Consistent Statistics for Anomaly Detection in Dynamic Networks. CoRR (2016)
Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, Nick G. Duffield
Fast Parallel Graphlet Counting for Large Networks. CoRR (2015)
Pablo Robles-Granda, Sebastián Moreno, Jennifer Neville
Using Bayesian Network Representations for Effective Sampling from Generative Network Models. CoRR (2015)
Ransen Niu, Sebastián Moreno, Jennifer Neville
Analyzing the Transferability of Collective Inference Models Across Networks. ICDM Workshops (2015)
Stephen Mussmann, John Moore, Joseph John Pfeiffer III, Jennifer Neville
Incorporating Assortativity and Degree Dependence into Scalable Network Models. AAAI (2015)
Joseph J. Pfeiffer III, Jennifer Neville, Paul N. Bennett
Overcoming Relational Learning Biases to Accurately Predict Preferences in Large Scale Networks. WWW (2015)
Nesreen K. Ahmed, Jennifer Neville, Ryan A. Rossi, Nick G. Duffield
Efficient Graphlet Counting for Large Networks. ICDM (2015)
Joseph J. Pfeiffer III, Sebastián Moreno, Timothy La Fond, Jennifer Neville, Brian Gallagher
Attributed graph models: modeling network structure with correlated attributes. WWW (2014)
Nesreen K. Ahmed, Nick G. Duffield, Jennifer Neville, Ramana Rao Kompella
Graph Sample and Hold: A Framework for Big-Graph Analytics. CoRR (2014)
Nesreen K. Ahmed, Nick G. Duffield, Jennifer Neville, Ramana Rao Kompella
Graph sample and hold: a framework for big-graph analytics. KDD (2014)
Georgios B. Giannakis, Francis R. Bach, Raphael Cendrillon, Michael W. Mahoney, Jennifer Neville
Signal Processing for Big Data [From the Guest Editors]. IEEE Signal Process. Mag. 31 (5) (2014)
Sebastián Moreno, Joseph J. Pfeiffer III, Jennifer Neville, Sergey Kirshner
A Scalable Method for Exact Sampling from Kronecker Family Models. ICDM (2014)
Nesreen K. Ahmed, Christopher Cole, Jennifer Neville
Learning the Latent State Space of Time-Varying Graphs. CoRR (2014)
Stephen Mussmann, John Moore, Joseph J. Pfeiffer III, Jennifer Neville
Assortativity in Chung Lu Random Graph Models. SNAKDD (2014)
Joseph John Pfeiffer III, Jennifer Neville, Paul N. Bennett
Active Exploration in Networks: Using Probabilistic Relationships for Learning and Inference. CIKM (2014)
Timothy La Fond, Jennifer Neville, Brian Gallagher
Anomaly Detection in Dynamic Networks of Varying Size. CoRR (2014)
Joseph J. Pfeiffer III, Jennifer Neville, Paul N. Bennett
Composite Likelihood Data Augmentation for Within-Network Statistical Relational Learning. ICDM (2014)
Ryan A. Rossi, Brian Gallagher, Jennifer Neville, Keith Henderson
Modeling dynamic behavior in large evolving graphs. WSDM (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jennifer Neville