Non-Expert Correction of Automatically Generated Relation Annotations. - Matthew R. Gormley; Adam Gerber; Mary P. Harper; Mark Dredze (Mturk@HLT-NAACL, 2010)

Shared Components Topic Models. - Matthew R. Gormley; Mark Dredze; Benjamin Van Durme; Jason Eisner (HLT-NAACL, 2012)

Entity Clustering Across Languages. - Spence Green; Nicholas Andrews; Matthew R. Gormley; Mark Dredze; Christopher D. Manning (HLT-NAACL, 2012)

Annotated Gigaword. - Courtney Napoles; Matthew Gormley 001; Benjamin Van Durme (AKBC-WEKEX@NAACL-HLT, 2012)

Nonconvex Global Optimization for Latent-Variable Models. - Matthew R. Gormley; Jason Eisner (ACL (1), 2013)

Topic Models and Metadata for Visualizing Text Corpora. - Justin Snyder; Rebecca Knowles; Mark Dredze; Matthew Gormley 001; Travis Wolfe (HLT-NAACL, 2013)

Structured Belief Propagation for NLP. - Matthew Gormley 001; Jason Eisner (ACL (Tutorial Abstracts), 2014)

Low-Resource Semantic Role Labeling. - Matthew R. Gormley; Margaret Mitchell; Benjamin Van Durme; Mark Dredze (ACL (1), 2014)

Improved Relation Extraction with Feature-Rich Compositional Embedding Models. - Matthew R. Gormley; Mo Yu; Mark Dredze (EMNLP, 2015)

A Concrete Chinese NLP Pipeline. - Nanyun Peng 001; Francis Ferraro; Mo Yu; Nicholas Andrews; Jay DeYoung; Max Thomas; Matthew R. Gormley; Travis Wolfe; Craig Harman; Benjamin Van Durme; Mark Dredze (HLT-NAACL, 2015)

Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction. - Mo Yu; Matthew R. Gormley; Mark Dredze (HLT-NAACL, 2015)

Approximation-Aware Dependency Parsing by Belief Propagation. - Matthew R. Gormley; Mark Dredze; Jason Eisner (Trans. Assoc. Comput. Linguistics, 2015)

Embedding Lexical Features via Low-Rank Tensors. - Mo Yu; Mark Dredze; Raman Arora; Matthew R. Gormley (HLT-NAACL, 2016)

Semantic Proto-Role Labeling. - Adam R. Teichert; Adam Poliak; Benjamin Van Durme; Matthew Gormley 001 (AAAI, 2017)

Neural Factor Graph Models for Cross-lingual Morphological Tagging. - Chaitanya Malaviya; Matthew R. Gormley; Graham Neubig (ACL (1), 2018)

Learning Beam Search Policies via Imitation Learning. - Renato Negrinho; Matthew Gormley 001; Geoffrey J. Gordon (NeurIPS, 2018)

Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces. - Barun Patra; Joel Ruben Antony Moniz; Sarthak Garg; Matthew R. Gormley; Graham Neubig (ACL (1), 2019)

Neural Finite-State Transducers: Beyond Rational Relations. - Chu-Cheng Lin; Hao Zhu; Matthew R. Gormley; Jason Eisner (NAACL-HLT (1), 2019)

Towards modular and programmable architecture search. - Renato Negrinho; Matthew Gormley 001; Geoffrey J. Gordon; Darshan Patil; Nghia Le; Daniel Ferreira (NeurIPS, 2019)

Phonetic and Visual Priors for Decipherment of Informal Romanization. - Maria Ryskina; Matthew R. Gormley; Taylor Berg-Kirkpatrick (ACL, 2020)

Training for Gibbs Sampling on Conditional Random Fields with Neural Scoring Factors. - Sida Gao; Matthew R. Gormley (EMNLP (1), 2020)

An Empirical Investigation of Beam-Aware Training in Supertagging. - Renato Negrinho; Matthew R. Gormley; Geoffrey J. Gordon (EMNLP (Findings), 2020)

Autoregressive Modeling is Misspecified for Some Sequence Distributions. - Chu-Cheng Lin; Aaron Jaech; Xin Li; Matthew R. Gormley; Jason Eisner (CoRR, 2020)

Effective Convolutional Attention Network for Multi-label Clinical Document Classification. - Yang Liu; Hua Cheng; Russell Klopfer; Matthew R. Gormley; Thomas Schaaf (EMNLP (1), 2021)

Leveraging Pretrained Models for Automatic Summarization of Doctor-Patient Conversations. - Longxiang Zhang; Renato Negrinho; Arindam Ghosh; Vasudevan Jagannathan; Hamid Reza Hassanzadeh; Thomas Schaaf; Matthew R. Gormley (EMNLP (Findings), 2021)

Limitations of Autoregressive Models and Their Alternatives. - Chu-Cheng Lin; Aaron Jaech; Xin Li; Matthew R. Gormley; Jason Eisner (NAACL-HLT, 2021)

Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction. - Maria Ryskina; Eduard H. Hovy; Taylor Berg-Kirkpatrick; Matthew R. Gormley (CoRR, 2021)

On Efficiently Acquiring Annotations for Multilingual Models. - Joel Ruben Antony Moniz; Barun Patra; Matthew Gormley 001 (ACL (2), 2022)

He Said, She Said: Style Transfer for Shifting the Perspective of Dialogues. - Amanda Bertsch; Graham Neubig; Matthew R. Gormley (EMNLP (Findings), 2022)

AdaFocal: Calibration-aware Adaptive Focal Loss. - Arindam Ghosh; Thomas Schaaf; Matthew Gormley 001 (NeurIPS, 2022)

Revisiting text decomposition methods for NLI-based factuality scoring of summaries. - John Glover; Federico Fancellu; Vasudevan Jagannathan; Matthew R. Gormley; Thomas Schaaf (CoRR, 2022)

SummQA at MEDIQA-Chat 2023: In-Context Learning with GPT-4 for Medical Summarization. - Yash Mathur; Sanketh Rangreji; Raghav Kapoor; Medha Palavalli; Amanda Bertsch; Matthew Gormley 001 (ClinicalNLP@ACL, 2023)

MDACE: MIMIC Documents Annotated with Code Evidence. - Hua Cheng; Rana Jafari; April Russell; Russell Klopfer; Edmond Lu; Benjamin Striner; Matthew Gormley 001 (ACL (1), 2023)

Unlimiformer: Long-Range Transformers with Unlimited Length Input. - Amanda Bertsch; Uri Alon 002; Graham Neubig; Matthew Gormley 001 (NeurIPS, 2023)

It's MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk. - Amanda Bertsch; Alex Xie; Graham Neubig; Matthew R. Gormley (CoRR, 2023)

A Taxonomy for Data Contamination in Large Language Models. - Medha Palavalli; Amanda Bertsch; Matthew Gormley 001 (CONDA, 2024)

Learning Mutually Informed Representations for Characters and Subwords. - Yilin Wang; Xinyi Hu; Matthew Gormley 001 (NAACL-HLT (Findings), 2024)

In-Context Learning with Long-Context Models: An In-Depth Exploration. - Amanda Bertsch; Maor Ivgi; Uri Alon 002; Jonathan Berant; Matthew R. Gormley; Graham Neubig (CoRR, 2024)

Improving Autoregressive Training with Dynamic Oracles. - Jianing Yang; Harshine Visvanathan; Yilin Wang; Xinyi Hu; Matthew Gormley 001 (CoRR, 2024)

In-Context Learning with Long-Context Models: An In-Depth Exploration. - Amanda Bertsch; Maor Ivgi; Emily Xiao; Uri Alon 002; Jonathan Berant; Matthew R. Gormley; Graham Neubig (NAACL (Long Papers), 2025)

Larger than Life In-Class Demonstrations for Introductory Machine Learning. - Henry Chai; Matthew R. Gormley (SIGCSE (1), 2025)

Predicting the Past: Estimating Historical Appraisals with OCR and Machine Learning. - Mihir Bhaskar; Jun Tao Luo; Zihan Geng; Asmita Hajra; Junia Howell; Matthew R. Gormley (CoRR, 2025)