An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction. - Stefan Larson; Anish Mahendran; Joseph J. Peper; Christopher Clarke; Andrew Lee 001; Parker Hill; Jonathan K. Kummerfeld; Kevin Leach; Michael A. Laurenzano; Lingjia Tang; Jason Mars (EMNLP/IJCNLP (1), 2019)

Outlier Detection for Improved Data Quality and Diversity in Dialog Systems. - Stefan Larson; Anish Mahendran; Andrew Lee 001; Jonathan K. Kummerfeld; Parker Hill; Michael A. Laurenzano; Johann Hauswald; Lingjia Tang; Jason Mars (NAACL-HLT (1), 2019)

Micromodels for Efficient, Explainable, and Reusable Systems: A Case Study on Mental Health. - Andrew Lee 001; Jonathan K. Kummerfeld; Larry An; Rada Mihalcea (EMNLP (Findings), 2021)

Augmenting Task-Oriented Dialogue Systems with Relation Extraction. - Andrew Lee 001; Zhenguo Chen; Kevin Leach; Jonathan K. Kummerfeld (CoRR, 2022)

Improving Chess Commentaries by Combining Language Models with Symbolic Reasoning Engines. - Andrew Lee 001; David Wu; Emily Dinan; Mike Lewis (CoRR, 2022)

Emergent Linear Representations in World Models of Self-Supervised Sequence Models. - Neel Nanda; Andrew Lee 001; Martin Wattenberg (BlackboxNLP@EMNLP, 2023)

Empathy Identification Systems are not Accurately Accounting for Context. - Andrew Lee 001; Jonathan K. Kummerfeld; Larry An; Rada Mihalcea (EACL, 2023)

A PhD Student's Perspective on Research in NLP in the Era of Very Large Language Models. - Oana Ignat; Zhijing Jin 001; Artem Abzaliev; Laura Biester; Santiago Castro; Naihao Deng; Xinyi Gao 004; Aylin Gunal; Jacky He; Ashkan Kazemi; Muhammad Khalifa; Namho Koh; et al. (CoRR, 2023)

Some things are more CRINGE than others: Preference Optimization with the Pairwise Cringe Loss. - Jing Xu; Andrew Lee 001; Sainbayar Sukhbaatar; Jason Weston (CoRR, 2023)

Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models. - Oana Ignat; Zhijing Jin 001; Artem Abzaliev; Laura Biester; Santiago Castro; Naihao Deng; Xinyi Gao 004; Aylin Gunal; Jacky He; Ashkan Kazemi; Muhammad Khalifa; Namho Koh; et al. (LREC/COLING, 2024)

Towards Algorithmic Fidelity: Mental Health Representation across Demographics in Synthetic vs. Human-generated Data. - Shinka Mori; Oana Ignat; Andrew Lee 001; Rada Mihalcea (LREC/COLING, 2024)

A Comparative Multidimensional Analysis of Empathetic Systems. - Andrew Lee 001; Jonathan K. Kummerfeld; Lawrence C. An; Rada Mihalcea (EACL (1), 2024)

A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity. - Andrew Lee 001; Xiaoyan Bai; Itamar Pres; Martin Wattenberg; Jonathan K. Kummerfeld; Rada Mihalcea (ICML, 2024)

Emergence of Hidden Capabilities: Exploring Learning Dynamics in Concept Space. - Core Francisco Park; Maya Okawa; Andrew Lee 001; Ekdeep Singh Lubana; Hidenori Tanaka (NeurIPS, 2024)

Interpretability and Controllability in the Age of Language Models - Andrew Lee 001 (2024)

Eeyore: Realistic Depression Simulation via Expert-in-the-Loop Supervised and Preference Optimization. - Siyang Liu 003; Bianca Brie; Wenda Li; Laura Biester; Andrew Lee 001; James W. Pennebaker; Rada Mihalcea (ACL (Findings), 2025)

ICLR: In-Context Learning of Representations. - Core Francisco Park; Andrew Lee 001; Ekdeep Singh Lubana; Yongyi Yang; Maya Okawa; Kento Nishi; Martin Wattenberg; Hidenori Tanaka (ICLR, 2025)

Eeyore: Realistic Depression Simulation via Supervised and Preference Optimization. - Siyang Liu 003; Bianca Brie; Wenda Li; Laura Biester; Andrew Lee 001; James W. Pennebaker; Rada Mihalcea (CoRR, 2025)

Shared Global and Local Geometry of Language Model Embeddings. - Andrew Lee 001; Melanie Weber 001; Fernanda B. Viégas; Martin Wattenberg (CoRR, 2025)

The Geometry of Self-Verification in a Task-Specific Reasoning Model. - Andrew Lee 001; Lihao Sun; Chris Wendler; Fernanda B. Viégas; Martin Wattenberg (CoRR, 2025)