Detecting insider threats in a real corporate database of computer usage activity. - Ted E. Senator; Henry G. Goldberg; Alex Memory; William T. Young; Brad Rees; Robert Pierce; Daniel Huang 003; Matthew Reardon; David A. Bader; Edmond Chow; Irfan A. Essa; Joshua Jones; et al. (KDD, 2013)

Fast anomaly detection despite the duplicates. - Jay Yoon Lee; U Kang; Danai Koutra; Christos Faloutsos (WWW (Companion Volume), 2013)

Net-Ray: Visualizing and Mining Billion-Scale Graphs. - U Kang; Jay Yoon Lee; Danai Koutra; Christos Faloutsos (PAKDD (1), 2014)

Influence Propagation: Patterns, Model and a Case Study. - Yibin Lin; Agha Ali Raza; Jay Yoon Lee; Danai Koutra; Roni Rosenfeld; Christos Faloutsos (PAKDD (1), 2014)

Enforcing Output Constraints via SGD: A Step Towards Neural Lagrangian Relaxation. - Jay Yoon Lee; Michael L. Wick; Jean-Baptiste Tristan; Jaime G. Carbonell (AKBC@NIPS, 2017)

Enforcing Constraints on Outputs with Unconstrained Inference. - Jay Yoon Lee; Michael L. Wick; Jean-Baptiste Tristan; Jaime G. Carbonell (CoRR, 2017)

Towards Semi-Supervised Learning for Deep Semantic Role Labeling. - Sanket Vaibhav Mehta; Jay Yoon Lee; Jaime G. Carbonell (EMNLP, 2018)

Gradient-Based Inference for Networks with Output Constraints. - Jay Yoon Lee; Sanket Vaibhav Mehta; Michael L. Wick; Jean-Baptiste Tristan; Jaime G. Carbonell (AAAI, 2019)

Semi-Supervised Learning on Meta Structure: Multi-Task Tagging and Parsing in Low-Resource Scenarios. - Kyungtae Lim; Jay Yoon Lee; Jaime G. Carbonell; Thierry Poibeau (AAAI, 2020)

StructSum: Incorporating Latent and Explicit Sentence Dependencies for Single Document Summarization. - Vidhisha Balachandran; Artidoro Pagnoni; Jay Yoon Lee; Dheeraj Rajagopal; Jaime G. Carbonell; Yulia Tsvetkov (CoRR, 2020)

StructSum: Summarization via Structured Representations. - Vidhisha Balachandran; Artidoro Pagnoni; Jay Yoon Lee; Dheeraj Rajagopal; Jaime G. Carbonell; Yulia Tsvetkov (EACL, 2021)

Case-based Reasoning for Natural Language Queries over Knowledge Bases. - Rajarshi Das; Manzil Zaheer; Dung Thai; Ameya Godbole; Ethan Perez; Jay Yoon Lee; Lizhen Tan; Lazaros Polymenakos; Andrew McCallum (EMNLP (1), 2021)

Improved Latent Tree Induction with Distant Supervision via Span Constraints. - Zhiyang Xu; Andrew Drozdov; Jay-Yoon Lee; Tim O'Gorman; Subendhu Rongali; Dylan Finkbeiner; Shilpa Suresh; Mohit Iyyer; Andrew McCallum (EMNLP (1), 2021)

Event-Event Relation Extraction using Probabilistic Box Embedding. - EunJeong Hwang; Jay-Yoon Lee; Tianyi Yang; Dhruvesh Patel; Dongxu Zhang; Andrew McCallum (ACL (2), 2022)

Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-Learning. - Trapit Bansal; Salaheddin Alzubi; Tong Wang 012; Jay-Yoon Lee; Andrew McCallum (AutoML, 2022)

Modeling Label Space Interactions in Multi-label Classification using Box Embeddings. - Dhruvesh Patel; Pavitra Dangati; Jay-Yoon Lee; Michael Boratko; Andrew McCallum (ICLR, 2022)

Structured Energy Network As a Loss. - Jay Yoon Lee; Dhruvesh Patel; Purujit Goyal; Wenlong Zhao 001; Zhiyang Xu; Andrew McCallum (NeurIPS, 2022)

Learning from a Friend: Improving Event Extraction via Self-Training with Feedback from Abstract Meaning Representation. - Zhiyang Xu; Jay Yoon Lee; Lifu Huang (ACL (Findings), 2023)

Machine Reading Comprehension using Case-based Reasoning. - Dung Thai; Dhruv Agarwal 003; Mudit Chaudhary; Wenlong Zhao 001; Rajarshi Das; Jay-Yoon Lee; Hannaneh Hajishirzi; Manzil Zaheer; Andrew McCallum (EMNLP (Findings), 2023)

Multistage Collaborative Knowledge Distillation from Large Language Models. - Jiachen Zhao; Wenlong Zhao 001; Andrew Drozdov; Benjamin Rozonoyer; Md. Arafat Sultan; Jay-Yoon Lee; Mohit Iyyer; Andrew McCallum (CoRR, 2023)

An Analysis under a Unified Formulation of Learning Algorithms with Output Constraints. - Mooho Song; Jay-Yoon Lee (ACL (Student Research Workshop), 2024)

Multistage Collaborative Knowledge Distillation from a Large Language Model for Semi-Supervised Sequence Generation. - Jiachen Zhao; Wenlong Zhao 001; Andrew Drozdov; Benjamin Rozonoyer; Md. Arafat Sultan; Jay-Yoon Lee; Mohit Iyyer; Andrew McCallum (ACL (1), 2024)

RE-RAG: Improving Open-Domain QA Performance and Interpretability with Relevance Estimator in Retrieval-Augmented Generation. - Kiseung Kim; Jay-Yoon Lee (EMNLP, 2024)

Towards Efficient Visual-Language Alignment of the Q-Former for Visual Reasoning Tasks. - Sungkyung Kim; Adam Lee; Junyoung Park; Andrew Chung; Jusang Oh; Jay-Yoon Lee (EMNLP (Findings), 2024)

Comparing Neighbors Together Makes it Easy: Jointly Comparing Multiple Candidates for Efficient and Effective Retrieval. - Jonghyun Song; Cheyon Jin; Wenlong Zhao 001; Andrew McCallum; Jay-Yoon Lee (EMNLP, 2024)

Comparing Neighbors Together Makes it Easy: Jointly Comparing Multiple Candidates for Efficient and Effective Retrieval. - Jonghyun Song; Cheyon Jin; Wenlong Zhao 001; Jay-Yoon Lee (CoRR, 2024)

Case-Based Reasoning Approach for Solving Financial Question Answering. - Yikyung Kim; Jay-Yoon Lee (CoRR, 2024)

An Analysis under a Unified Fomulation of Learning Algorithms with Output Constraints. - Mooho Song; Jay-Yoon Lee (CoRR, 2024)

Locate&Edit: Energy-based Text Editing for Efficient, Flexible, and Faithful Controlled Text Generation. - Hye Ryung Son; Jay-Yoon Lee (CoRR, 2024)

Enhancing Robustness of Retrieval-Augmented Language Models with In-Context Learning. - Seong-Il Park; Seungwoo Choi; Na-Hyun Kim; Jay-Yoon Lee (CoRR, 2024)

QE-EBM: Using Quality Estimators as Energy Loss for Machine Translation. - Gahyun Yoo; Jay Yoon Lee (CoRR, 2024)

IntGrad MT: Eliciting LLMs' Machine Translation Capabilities with Sentence Interpolation and Gradual MT. - Seungwoo Choi; Gahyun Yoo; Jay-Yoon Lee (CoRR, 2024)

Toward Robust RALMs: Revealing the Impact of Imperfect Retrieval on Retrieval-Augmented Language Models. - Seong-Il Park; Jay-Yoon Lee (Trans. Assoc. Comput. Linguistics, 2024)

BridG MT: Enhancing LLMs' Machine Translation Capabilities with Sentence Bridging and Gradual MT. - Seungwoo Choi; Gahyun Yoo; Jay-Yoon Lee (ACL (Findings), 2025)

Introducing Verification Task of Set Consistency with Set-Consistency Energy Networks. - Mooho Song; Hye Ryung Son; Jay-Yoon Lee (ACL (1), 2025)

Improving NMT Models by Retrofitting Quality Estimators into Trainable Energy Loss. - Gahyun Yoo; Jay Yoon Lee (COLING, 2025)

CoMRes: Semi-Supervised Time Series Forecasting Utilizing Consensus Promotion of Multi-Resolution. - Yunju Cho; Jay-Yoon Lee (ICLR, 2025)

Mind the Gap: Aligning the Brain with Language Models Requires a Nonlinear and Multimodal Approach. - Danny Dongyeop Han; Yunju Cho; Jiook Cha; Jay-Yoon Lee (CoRR, 2025)

GraphCheck: Multi-Path Fact-Checking with Entity-Relationship Graphs. - Hyewon Jeon; Jay-Yoon Lee (CoRR, 2025)

Introducing Verification Task of Set Consistency with Set-Consistency Energy Networks. - Mooho Song; Hyeryung Son; Jay-Yoon Lee (CoRR, 2025)