Using classifier cascades for scalable e-mail classification. - Jay Pujara; Hal Daumé III; Lise Getoor (CEAS, 2011)

Large-Scale Knowledge Graph Identification Using PSL. - Jay Pujara; Hui Miao 001; Lise Getoor; William W. Cohen (AAAI Fall Symposia, 2013)

Ontology-aware partitioning for knowledge graph identification. - Jay Pujara; Hui Miao 001; Lise Getoor; William W. Cohen (AKBC@CIKM, 2013)

Knowledge Graph Identification. - Jay Pujara; Hui Miao 001; Lise Getoor; William W. Cohen (ISWC (1), 2013)

RELLY: Inferring Hypernym Relationships Between Relational Phrases. - Adam Grycner; Gerhard Weikum; Jay Pujara; James R. Foulds; Lise Getoor (EMNLP, 2015)

Budgeted Online Collective Inference. - Jay Pujara; Ben London 001; Lise Getoor (UAI, 2015)

Using Semantics and Statistics to Turn Data into Knowledge. - Jay Pujara; Hui Miao 001; Lise Getoor; William W. Cohen (AI Mag., 2015)

Unsupervised models for predicting strategic relations between organizations. - Shachi H. Kumar; Jay Pujara; Lise Getoor; David Mares; Dipak Gupta; Ellen Riloff (ASONAM, 2016)

Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks. - Shobeir Fakhraei; Dhanya Sridhar; Jay Pujara; Lise Getoor (CoRR, 2016)

Generic Statistical Relational Entity Resolution in Knowledge Graphs. - Jay Pujara; Lise Getoor (CoRR, 2016)

Probabilistic Models for Scalable Knowledge Graph Construction. - Jay Pujara (2016)

Using Noisy Extractions to Discover Causal Knowledge. - Dhanya Sridhar; Jay Pujara; Lise Getoor (AKBC@NIPS, 2017)

Sparsity and Noise: Where Knowledge Graph Embeddings Fall Short. - Jay Pujara; Eriq Augustine; Lise Getoor (EMNLP, 2017)

Collective Entity Resolution in Familial Networks. - Pigi Kouki; Jay Pujara; Christopher Marcum; Laura M. Koehly; Lise Getoor (ICDM, 2017)

Disambiguating Energy Disaggregation: A Collective Probabilistic Approach. - Sabina Tomkins; Jay Pujara; Lise Getoor (IJCAI, 2017)

User Preferences for Hybrid Explanations. - Pigi Kouki; James Schaffer; Jay Pujara; John O'Donovan; Lise Getoor (RecSys, 2017)

Extracting Knowledge Graphs from Financial Filings: Extended Abstract. - Jay Pujara (DSMM@SIGMOD, 2017)

Probabilistic Visitor Stitching on Cross-Device Web Logs. - Sungchul Kim; Nikhil Kini; Jay Pujara; Eunyee Koh; Lise Getoor (WWW, 2017)

Scalable Probabilistic Causal Structure Discovery. - Dhanya Sridhar; Jay Pujara; Lise Getoor (IJCAI, 2018)

Feature Selection Methods For Understanding Business Competitor Relationships. - Rahul Gupta; Jay Pujara; Craig A. Knoblock; Shushyam M. Sharanappa; Bharat Pulavarti; Gerard Hoberg; Gordon Phillips (DSMM@SIGMOD, 2018)

Hybrid Link Prediction for Competitor Relationships. - Jay Pujara (DSMM@SIGMOD, 2018)

Financial Entity Identification and Information Integration (FEIII) 2018 Challenge: The Report of the Organizing Committee. - Louiqa Raschid; Douglas Burdick; John Grant; Joe Langsam; Jay Pujara; Elizabeth Roman; Ian Soboroff; Mohammed J. Zaki; Elena Zotkina (DSMM@SIGMOD, 2018)

Mining Knowledge Graphs From Text. - Jay Pujara; Sameer Singh 001 (WSDM, 2018)

Learning Data Transformations with Minimal User Effort. - Minh Pham 004; Craig A. Knoblock; Jay Pujara (IEEE BigData, 2019)

Tabular Cell Classification Using Pre-Trained Cell Embeddings. - Majid Ghasemi-Gol; Jay Pujara; Pedro A. Szekely (ICDM, 2019)

An intelligent interface for integrating climate, hydrology, agriculture, and socioeconomic models. - Daniel Garijo; Deborah Khider; Varun Ratnakar; Yolanda Gil; Ewa Deelman; Rafael Ferreira da Silva; Craig A. Knoblock; Yao-Yi Chiang; Minh Pham 004; Jay Pujara; Binh Vu; Dan Feldman; et al. (IUI Companion, 2019)

Personalized explanations for hybrid recommender systems. - Pigi Kouki; James Schaffer; Jay Pujara; John O'Donovan; Lise Getoor (IUI, 2019)

T2WML: Table To Wikidata Mapping Language. - Pedro A. Szekely; Daniel Garijo; Divij Bhatia; Jiasheng Wu; Yixiang Yao; Jay Pujara (K-CAP, 2019)

D-REPR: A Language for Describing and Mapping Diversely-Structured Data Sources to RDF. - Binh Vu; Jay Pujara; Craig A. Knoblock (K-CAP, 2019)

A Common Framework for Developing Table Understanding Models. - Jay Pujara; Arunkumar Rajendran; Majid Ghasemi-Gol; Pedro A. Szekely (ISWC (Satellites), 2019)

T2WML: A Cell-Based Language to Map Tables into Wikidata Records. - Pedro A. Szekely; Daniel Garijo; Jay Pujara; Divij Bhatia; Jiasheng Wu (ISWC (Satellites), 2019)

Entity Linking to Knowledge Graphs to Infer Column Types and Properties. - Avijit Thawani; Minda Hu; Erdong Hu; Husain Zafar; Naren Teja Divvala; Amandeep Singh; Ehsan Qasemi; Pedro A. Szekely; Jay Pujara (SemTab@ISWC, 2019)

Financial Entity Identification and Information Integration (FEIII) 2019 Challenge: The Report of the Organizing Committee. - Louiqa Raschid; Douglas Burdick; Cesar de Pablo; Mark D. Flood; John Grant; Joe Langsam; Jay Pujara; Elena Tomas; Ian Soboroff (DSMM@SIGMOD, 2019)

Extensible and Scalable Entity Resolution for Financial Datasets Using RLTK. - Yixiang Yao; Pedro A. Szekely; Jay Pujara (DSMM@SIGMOD, 2019)

Learning Semantic Models of Data Sources Using Probabilistic Graphical Models. - Binh Vu; Craig A. Knoblock; Jay Pujara (WWW, 2019)

Statistical investigation of surface roughness and kerf on wire electrical discharge machining performance. - Jay Pujara; Kartik D. Kothari; Ashish V. Gohil (Int. J. Manuf. Res., 2019)

Collective entity resolution in multi-relational familial networks. - Pigi Kouki; Jay Pujara; Christopher Marcum; Laura M. Koehly; Lise Getoor (Knowl. Inf. Syst., 2019)

Human-like Time Series Summaries via Trend Utility Estimation. - Pegah Jandaghi; Jay Pujara (CoRR, 2020)

Can BERT Reason? Logically Equivalent Probes for Evaluating the Inference Capabilities of Language Models. - Pei Zhou; Rahul Khanna; Bill Yuchen Lin; Daniel Ho; Xiang Ren 001; Jay Pujara (CoRR, 2020)

Generating and Understanding Personalized Explanations in Hybrid Recommender Systems. - Pigi Kouki; James Schaffer; Jay Pujara; John O'Donovan; Lise Getoor (ACM Trans. Interact. Intell. Syst., 2020)

A Hybrid Probabilistic Approach for Table Understanding. - Kexuan Sun 002; Harsha Rayudu; Jay Pujara (AAAI, 2021)

Tabular Functional Block Detection with Embedding-based Agglomerative Cell Clustering. - Kexuan Sun 002; Fei Wang 060; Muhao Chen 001; Jay Pujara (CIKM, 2021)

Table-based Fact Verification With Salience-aware Learning. - Fei Wang 060; Kexuan Sun 002; Jay Pujara; Pedro A. Szekely; Muhao Chen 001 (EMNLP (Findings), 2021)

Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources. - Ninareh Mehrabi; Pei Zhou; Fred Morstatter; Jay Pujara; Xiang Ren 001; Aram Galstyan (EMNLP (1), 2021)

Numeracy enhances the Literacy of Language Models. - Avijit Thawani; Jay Pujara; Filip Ilievski (EMNLP (1), 2021)

Probing Commonsense Explanation in Dialogue Response Generation. - Pei Zhou; Pegah Jandaghi; Hyundong Cho; Bill Yuchen Lin; Jay Pujara; Xiang Ren 001 (EMNLP (Findings), 2021)

RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms. - Pei Zhou; Rahul Khanna; Seyeon Lee; Bill Yuchen Lin; Daniel Ho; Jay Pujara; Xiang Ren 001 (EMNLP (1), 2021)

SPADE: A Semi-supervised Probabilistic Approach for Detecting Errors in Tables. - Minh Pham 004; Craig A. Knoblock; Muhao Chen 001; Binh Vu; Jay Pujara (IJCAI, 2021)

From Tables to Knowledge: Recent Advances in Table Understanding. - Jay Pujara; Pedro A. Szekely; Huan Sun 001; Muhao Chen 001 (KDD, 2021)

Representing Numbers in NLP: a Survey and a Vision. - Avijit Thawani; Jay Pujara; Filip Ilievski; Pedro A. Szekely (NAACL-HLT, 2021)

A Graph-Based Approach for Inferring Semantic Descriptions of Wikipedia Tables. - Binh Vu; Craig A. Knoblock; Pedro A. Szekely; Minh Pham 004; Jay Pujara (ISWC, 2021)

Commonsense-Focused Dialogues for Response Generation: An Empirical Study. - Pei Zhou; Karthik Gopalakrishnan 001; Behnam Hedayatnia; Seokhwan Kim; Jay Pujara; Xiang Ren 001; Yang Liu 004; Dilek Hakkani-Tür (SIGDIAL, 2021)

Retrieving Complex Tables with Multi-Granular Graph Representation Learning. - Fei Wang 060; Kexuan Sun 002; Muhao Chen 001; Jay Pujara; Pedro A. Szekely (SIGIR, 2021)

Probing Causal Common Sense in Dialogue Response Generation. - Pei Zhou; Pegah Jandaghi; Bill Yuchen Lin; Justin Cho; Jay Pujara; Xiang Ren 001 (CoRR, 2021)

AutoTriggER: Named Entity Recognition with Auxiliary Trigger Extraction. - Dong-Ho Lee; Ravi Kiran Selvam; Sheikh Muhammad Sarwar; Bill Yuchen Lin; Mahak Agarwal; Fred Morstatter; Jay Pujara; Elizabeth Boschee; James Allan; Xiang Ren 001 (CoRR, 2021)

Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER. - Dong-Ho Lee; Mahak Agarwal; Akshen Kadakia; Jay Pujara; Xiang Ren 001 (CoRR, 2021)

Think Before You Speak: Using Self-talk to Generate Implicit Commonsense Knowledge for Response Generation. - Pei Zhou; Karthik Gopalakrishnan 001; Behnam Hedayatnia; Seokhwan Kim; Jay Pujara; Xiang Ren 001; Yang Liu 004; Dilek Hakkani-Tur (CoRR, 2021)

Learning cell embeddings for understanding table layouts. - Majid Ghasemi-Gol; Jay Pujara; Pedro A. Szekely (Knowl. Inf. Syst., 2021)

Artificial Intelligence for Modeling Complex Systems: Taming the Complexity of Expert Models to Improve Decision Making. - Yolanda Gil; Daniel Garijo; Deborah Khider; Craig A. Knoblock; Varun Ratnakar; Maximiliano Osorio; Hernán Vargas; Minh Pham 004; Jay Pujara; Basel Shbita; Binh Vu; Yao-Yi Chiang; et al. (ACM Trans. Interact. Intell. Syst., 2021)

Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-Modal Knowledge Transfer. - Woojeong Jin 001; Dong-Ho Lee; Chenguang Zhu 001; Jay Pujara; Xiang Ren 001 (ACL (1), 2022)

Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER. - Dong-Ho Lee; Akshen Kadakia; Kangmin Tan; Mahak Agarwal; Xinyu Feng; Takashi Shibuya 001; Ryosuke Mitani; Toshiyuki Sekiya; Jay Pujara; Xiang Ren 001 (ACL (1), 2022)

Think Before You Speak: Explicitly Generating Implicit Commonsense Knowledge for Response Generation. - Pei Zhou; Karthik Gopalakrishnan 001; Behnam Hedayatnia; Seokhwan Kim; Jay Pujara; Xiang Ren 001; Yang Liu 004; Dilek Hakkani-Tur (ACL (1), 2022)

FETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue. - Alon Albalak; Yi-Lin Tuan; Pegah Jandaghi; Connor Pryor; Luke Yoffe; Deepak Ramachandran; Lise Getoor; Jay Pujara; William Yang Wang (EMNLP, 2022)

Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response Quality. - Pei Zhou; Hyundong Cho; Pegah Jandaghi; Dong-Ho Lee; Bill Yuchen Lin; Jay Pujara; Xiang Ren 001 (EMNLP, 2022)

Does Wikidata Support Analogical Reasoning? - Filip Ilievski; Jay Pujara; Kartik Shenoy (KGSWC, 2022)

Visual Sudoku Puzzle Classification: A Suite of Collective Neuro-Symbolic Tasks. - Eriq Augustine; Connor Pryor; Charles Dickens; Jay Pujara; William Yang Wang; Lise Getoor (NeSy, 2022)

Assessing Scientific Research Papers with Knowledge Graphs. - Kexuan Sun 002; Zhiqiang Qiu; Abel Salinas; Yuzhong Huang; Dong-Ho Lee; Daniel Benjamin; Fred Morstatter; Xiang Ren 001; Kristina Lerman; Jay Pujara (SIGIR, 2022)

Evaluating Machine Common Sense via Cloze Testing. - Ehsan Qasemi; Lee Kezar; Jay Pujara; Pedro A. Szekely (CoRR, 2022)

Understanding Narratives through Dimensions of Analogy. - Thiloshon Nagarajah; Filip Ilievski; Jay Pujara (CoRR, 2022)

Seq2Seq-SC: End-to-End Semantic Communication Systems with Pre-trained Language Model. - Ju-Hyung Lee 001; Dong-Ho Lee; Eunsoo Sheen; Thomas Choi 001; Jay Pujara; Joongheon Kim (CoRR, 2022)

An AI Dungeon Master's Guide: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons. - Pei Zhou; Andrew Zhu; Jennifer Hu 001; Jay Pujara; Xiang Ren 001; Chris Callison-Burch; Yejin Choi 001; Prithviraj Ammanabrolu (CoRR, 2022)

Citation Intent Classification Through Weakly Supervised Knowledge Graphs. - Xinwei Du; Kian Ahrabian; Arun Baalaaji Sankar Ananthan; Richard Delwin Myloth; Jay Pujara (SDU@AAAI, 2023)

Is Dynamicity All You Need? - Richard Delwin Myloth; Kian Ahrabian; Arun Baalaaji Sankar Ananthan; Xinwei Du; Jay Pujara (SDU@AAAI, 2023)

XMD: An End-to-End Framework for Interactive Explanation-Based Debugging of NLP Models. - Dong-Ho Lee; Akshen Kadakia; Brihi Joshi; Aaron Chan; Ziyi Liu 007; Kiran Narahari; Takashi Shibuya 001; Ryosuke Mitani; Toshiyuki Sekiya; Jay Pujara; Xiang Ren 001 (ACL (demo), 2023)

I Cast Detect Thoughts: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons. - Pei Zhou; Andrew Zhu; Jennifer Hu 001; Jay Pujara; Xiang Ren 001; Chris Callison-Burch; Yejin Choi 001; Prithviraj Ammanabrolu (ACL (1), 2023)

SEQ2SEQ-SC: End-To-End Semantic Communication Systems with Pre-Trained Language Model. - Ju-Hyung Lee 001; Dong-Ho Lee; Eunsoo Sheen; Thomas Choi 001; Jay Pujara (ACSSC, 2023)

AutoTriggER: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction. - Dong-Ho Lee; Ravi Kiran Selvam; Sheikh Muhammad Sarwar; Bill Yuchen Lin; Fred Morstatter; Jay Pujara; Elizabeth Boschee; James Allan; Xiang Ren 001 (EACL, 2023)

Temporal Knowledge Graph Forecasting Without Knowledge Using In-Context Learning. - Dong-Ho Lee; Kian Ahrabian; Woojeong Jin 001; Fred Morstatter; Jay Pujara (EMNLP, 2023)

Making Large Language Models Better Data Creators. - Dong-Ho Lee; Jay Pujara; Mohit Sewak; Ryen White; Sujay Kumar Jauhar (EMNLP, 2023)

Analyzing Norm Violations in Live-Stream Chat. - Jihyung Moon; Dong-Ho Lee; Hyundong Cho; Woojeong Jin 001; Chan Young Park; Minwoo Kim; Jonathan May; Jay Pujara; Sungjoon Park (EMNLP, 2023)

Learn Your Tokens: Word-Pooled Tokenization for Language Modeling. - Avijit Thawani; Saurabh Ghanekar; Xiaoyuan Zhu; Jay Pujara (EMNLP (Findings), 2023)

Comparison of Knowledge Graph Representations for Consumer Scenarios. - Ana Iglesias-Molina; Kian Ahrabian; Filip Ilievski; Jay Pujara; Óscar Corcho (ISWC, 2023)

PubGraph: A Large Scale Scientific Temporal Knowledge Graph. - Kian Ahrabian; Xinwei Du; Richard Delwin Myloth; Arun Baalaaji Sankar Ananthan; Jay Pujara (CoRR, 2023)

Finding Pragmatic Differences Between Disciplines. - Lee Kezar; Jay Pujara (CoRR, 2023)

How FaR Are Large Language Models From Agents with Theory-of-Mind? - Pei Zhou; Aman Madaan; Srividya Pranavi Potharaju; Aditya Gupta; Kevin R. McKee; Ari Holtzman; Jay Pujara; Xiang Ren 001; Swaroop Mishra; Aida Nematzadeh; Shyam Upadhyay; Manaal Faruqui (CoRR, 2023)

Estimating Numbers without Regression. - Avijit Thawani; Jay Pujara; Ashwin Kalyan (CoRR, 2023)

Building Robust and Explainable AI with Commonsense Knowledge Graphs and Neural Models. - Filip Ilievski; Kaixin Ma; Alessandro Oltramari; Peifeng Wang; Jay Pujara (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Knowledge-Powered Recommendation for an Improved Diet Water Footprint. - Saurav Joshi; Filip Ilievski; Jay Pujara (AAAI, 2024)

Faithful Persona-based Conversational Dataset Generation with Large Language Models. - Pegah Jandaghi; XiangHai Sheng; Xinyi Bai; Jay Pujara; Hakim Sidahmed (ACL (Findings), 2024)

Efficient and Accurate Contextual Re-Ranking for Knowledge Graph Question Answering. - Kexuan Sun 002; Nicolaas Paul Jedema; Karishma Sharma; Ruben Janssen; Jay Pujara; Pedro A. Szekely; Alessandro Moschitti (LREC/COLING, 2024)

On the Adaptation of Unlimiformer for Decoder-Only Transformers. - Kian Ahrabian; Alon Benhaim; Barun Patra; Jay Pujara; Saksham Singhal; Xia Song (LREC/COLING, 2024)

MARVEL: Multidimensional Abstraction and Reasoning through Visual Evaluation and Learning. - Yifan Jiang 001; Jiarui Zhang 002; Kexuan Sun 002; Zhivar Sourati; Kian Ahrabian; Kaixin Ma; Filip Ilievski; Jay Pujara (NeurIPS, 2024)

SELF-DISCOVER: Large Language Models Self-Compose Reasoning Structures. - Pei Zhou; Jay Pujara; Xiang Ren 001; Xinyun Chen; Heng-Tze Cheng; Quoc V. Le; Ed H. Chi; Denny Zhou; Swaroop Mishra; Huaixiu Steven Zheng (NeurIPS, 2024)

The Curious Case of Nonverbal Abstract Reasoning with Multi-Modal Large Language Models. - Kian Ahrabian; Zhivar Sourati; Kexuan Sun 002; Jiarui Zhang 002; Yifan Jiang 001; Fred Morstatter; Jay Pujara (CoRR, 2024)

The Hitchhiker's Guide to Human Alignment with *PO. - Kian Ahrabian; Xihui Lin; Barun Patra; Vishrav Chaudhary; Alon Benhaim; Jay Pujara; Xia Song (CoRR, 2024)

Surprising Resilience of Science During a Global Pandemic: A Large-Scale Descriptive Analysis. - Kian Ahrabian; Casandra Rusti; Ziao Wang; Jay Pujara; Kristina Lerman (CoRR, 2024)

RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking. - Yifan Jiang 001; Kriti Aggarwal; Tanmay Laud; Kashif Munir; Jay Pujara; Subhabrata Mukherjee (CoRR, 2024)

Integrating Pre-Trained Language Model With Physical Layer Communications. - Ju-Hyung Lee 001; Dong-Ho Lee; Joohan Lee; Jay Pujara (IEEE Trans. Wirel. Commun., 2024)

Red Queen: Exposing Latent Multi-Turn Risks in Large Language Models. - Yifan Jiang 001; Kriti Aggarwal; Tanmay Laud; Kashif Munir; Jay Pujara; Subhabrata Mukherjee (ACL (Findings), 2025)

A Practical Analysis of Human Alignment with *PO. - Kian Ahrabian; Xihui Lin; Barun Patra; Vishrav Chaudhary; Alon Benhaim; Jay Pujara; Xia Song (NAACL (Findings), 2025)

REALTALK: A 21-Day Real-World Dataset for Long-Term Conversation. - Dong-Ho Lee; Adyasha Maharana; Jay Pujara; Xiang Ren 001; Francesco Barbieri (CoRR, 2025)

What is a Good Question? Utility Estimation with LLM-based Simulations. - Dong-Ho Lee; Hyundong Cho; Jonathan May; Jay Pujara (CoRR, 2025)

A Systematic Analysis of Base Model Choice for Reward Modeling. - Kian Ahrabian; Pegah Jandaghi; Negar Mokhberian; Sai Praneeth Karimireddy; Jay Pujara (CoRR, 2025)