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2020 – today
- 2024
[c32]Yilin Wang, Xinyi Hu, Matthew R. Gormley:
Learning Mutually Informed Representations for Characters and Subwords. NAACL-HLT (Findings) 2024: 3201-3213- [i24]Amanda Bertsch, Maor Ivgi, Uri Alon, Jonathan Berant, Matthew R. Gormley, Graham Neubig:
In-Context Learning with Long-Context Models: An In-Depth Exploration. CoRR abs/2405.00200 (2024) - [i23]Jianing Yang, Harshine Visvanathan, Yilin Wang, Xinyi Hu, Matthew R. Gormley:
Improving Autoregressive Training with Dynamic Oracles. CoRR abs/2406.09393 (2024) - [i22]Medha Palavalli, Amanda Bertsch, Matthew R. Gormley:
A Taxonomy for Data Contamination in Large Language Models. CoRR abs/2407.08716 (2024) - 2023
- [c31]Hua Cheng, Rana Jafari, April Russell, Russell Klopfer, Edmond Lu, Benjamin Striner, Matthew R. Gormley:
MDACE: MIMIC Documents Annotated with Code Evidence. ACL (1) 2023: 7534-7550 - [c30]Yash Mathur, Sanketh Rangreji, Raghav Kapoor, Medha Palavalli, Amanda Bertsch, Matthew R. Gormley:
SummQA at MEDIQA-Chat 2023: In-Context Learning with GPT-4 for Medical Summarization. ClinicalNLP@ACL 2023: 490-502 - [c29]Amanda Bertsch, Uri Alon, Graham Neubig, Matthew R. Gormley:
Unlimiformer: Long-Range Transformers with Unlimited Length Input. NeurIPS 2023 - [i21]Amanda Bertsch, Uri Alon, Graham Neubig, Matthew R. Gormley:
Unlimiformer: Long-Range Transformers with Unlimited Length Input. CoRR abs/2305.01625 (2023) - [i20]Yash Mathur, Sanketh Rangreji, Raghav Kapoor, Medha Palavalli, Amanda Bertsch, Matthew R. Gormley:
SummQA at MEDIQA-Chat 2023: In-Context Learning with GPT-4 for Medical Summarization. CoRR abs/2306.17384 (2023) - [i19]Hua Cheng, Rana Jafari, April Russell, Russell Klopfer, Edmond Lu, Benjamin Striner, Matthew R. Gormley:
MDACE: MIMIC Documents Annotated with Code Evidence. CoRR abs/2307.03859 (2023) - [i18]Amanda Bertsch, Alex Xie, Graham Neubig, Matthew R. Gormley:
It's MBR All the Way Down: Modern Generation Techniques Through the Lens of Minimum Bayes Risk. CoRR abs/2310.01387 (2023) - [i17]Yilin Wang, Xinyi Hu, Matthew R. Gormley:
Learning Mutually Informed Representations for Characters and Subwords. CoRR abs/2311.07853 (2023) - 2022
- [c28]Joel Ruben Antony Moniz, Barun Patra, Matthew R. Gormley:
On Efficiently Acquiring Annotations for Multilingual Models. ACL (2) 2022: 69-85 - [c27]Amanda Bertsch, Graham Neubig, Matthew R. Gormley:
He Said, She Said: Style Transfer for Shifting the Perspective of Dialogues. EMNLP (Findings) 2022: 4823-4840 - [c26]Arindam Ghosh, Thomas Schaaf, Matthew R. Gormley:
AdaFocal: Calibration-aware Adaptive Focal Loss. NeurIPS 2022 - [i16]Joel Ruben Antony Moniz, Barun Patra, Matthew R. Gormley:
On Efficiently Acquiring Annotations for Multilingual Models. CoRR abs/2204.01016 (2022) - [i15]Amanda Bertsch, Graham Neubig, Matthew R. Gormley:
He Said, She Said: Style Transfer for Shifting the Perspective of Dialogues. CoRR abs/2210.15462 (2022) - [i14]Arindam Ghosh, Thomas Schaaf, Matthew R. Gormley:
AdaFocal: Calibration-aware Adaptive Focal Loss. CoRR abs/2211.11838 (2022) - [i13]John Glover, Federico Fancellu, Vasudevan Jagannathan, Matthew R. Gormley, Thomas Schaaf:
Revisiting text decomposition methods for NLI-based factuality scoring of summaries. CoRR abs/2211.16853 (2022) - 2021
- [c25]Longxiang Zhang, Renato Negrinho, Arindam Ghosh, Vasudevan Jagannathan, Hamid Reza Hassanzadeh, Thomas Schaaf, Matthew R. Gormley:
Leveraging Pretrained Models for Automatic Summarization of Doctor-Patient Conversations. EMNLP (Findings) 2021: 3693-3712 - [c24]Yang Liu, Hua Cheng, Russell Klopfer, Matthew R. Gormley, Thomas Schaaf:
Effective Convolutional Attention Network for Multi-label Clinical Document Classification. EMNLP (1) 2021: 5941-5953 - [c23]Chu-Cheng Lin, Aaron Jaech, Xin Li, Matthew R. Gormley, Jason Eisner:
Limitations of Autoregressive Models and Their Alternatives. NAACL-HLT 2021: 5147-5173 - [i12]Maria Ryskina, Eduard H. Hovy, Taylor Berg-Kirkpatrick, Matthew R. Gormley:
Comparative Error Analysis in Neural and Finite-state Models for Unsupervised Character-level Transduction. CoRR abs/2106.12698 (2021) - [i11]Longxiang Zhang, Renato Negrinho, Arindam Ghosh, Vasudevan Jagannathan, Hamid Reza Hassanzadeh, Thomas Schaaf, Matthew R. Gormley:
Leveraging Pretrained Models for Automatic Summarization of Doctor-Patient Conversations. CoRR abs/2109.12174 (2021) - 2020
- [c22]Maria Ryskina
, Matthew R. Gormley, Taylor Berg-Kirkpatrick:
Phonetic and Visual Priors for Decipherment of Informal Romanization. ACL 2020: 8308-8319 - [c21]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon:
An Empirical Investigation of Beam-Aware Training in Supertagging. EMNLP (Findings) 2020: 4534-4542 - [c20]Sida Gao, Matthew R. Gormley:
Training for Gibbs Sampling on Conditional Random Fields with Neural Scoring Factors. EMNLP (1) 2020: 4999-5011 - [i10]Maria Ryskina, Matthew R. Gormley, Taylor Berg-Kirkpatrick:
Phonetic and Visual Priors for Decipherment of Informal Romanization. CoRR abs/2005.02517 (2020) - [i9]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon:
An Empirical Investigation of Beam-Aware Training in Supertagging. CoRR abs/2010.04980 (2020) - [i8]Chu-Cheng Lin, Aaron Jaech, Xin Li, Matthew R. Gormley, Jason Eisner:
Autoregressive Modeling is Misspecified for Some Sequence Distributions. CoRR abs/2010.11939 (2020)
2010 – 2019
- 2019
- [c19]Barun Patra, Joel Ruben Antony Moniz, Sarthak Garg, Matthew R. Gormley, Graham Neubig:
Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces. ACL (1) 2019: 184-193 - [c18]Chu-Cheng Lin, Hao Zhu, Matthew R. Gormley, Jason Eisner:
Neural Finite-State Transducers: Beyond Rational Relations. NAACL-HLT (1) 2019: 272-283 - [c17]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon, Darshan Patil, Nghia Le, Daniel Ferreira:
Towards modular and programmable architecture search. NeurIPS 2019: 13715-13725 - [i7]Barun Patra, Joel Ruben Antony Moniz, Sarthak Garg, Matthew R. Gormley, Graham Neubig:
Bilingual Lexicon Induction with Semi-supervision in Non-Isometric Embedding Spaces. CoRR abs/1908.06625 (2019) - [i6]Renato Negrinho, Darshan Patil, Nghia Le, Daniel Ferreira, Matthew R. Gormley, Geoffrey J. Gordon:
Towards modular and programmable architecture search. CoRR abs/1909.13404 (2019) - 2018
- [c16]Chaitanya Malaviya, Matthew R. Gormley, Graham Neubig:
Neural Factor Graph Models for Cross-lingual Morphological Tagging. ACL (1) 2018: 2653-2663 - [c15]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon:
Learning Beam Search Policies via Imitation Learning. NeurIPS 2018: 10675-10684 - [i5]Chaitanya Malaviya, Matthew R. Gormley, Graham Neubig:
Neural Factor Graph Models for Cross-lingual Morphological Tagging. CoRR abs/1805.04570 (2018) - [i4]Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon:
Learning Beam Search Policies via Imitation Learning. CoRR abs/1811.00512 (2018) - 2017
- [c14]Adam R. Teichert, Adam Poliak, Benjamin Van Durme, Matthew R. Gormley:
Semantic Proto-Role Labeling. AAAI 2017: 4459-4466 - 2016
- [c13]Mo Yu, Mark Dredze, Raman Arora, Matthew R. Gormley:
Embedding Lexical Features via Low-Rank Tensors. HLT-NAACL 2016: 1019-1029 - [i3]Mo Yu, Mark Dredze, Raman Arora, Matthew R. Gormley:
Embedding Lexical Features via Low-Rank Tensors. CoRR abs/1604.00461 (2016) - 2015
- [j1]Matthew R. Gormley, Mark Dredze, Jason Eisner:
Approximation-Aware Dependency Parsing by Belief Propagation. Trans. Assoc. Comput. Linguistics 3: 489-501 (2015) - [c12]Matthew R. Gormley, Jason Eisner:
Structured Belief Propagation for NLP. ACL (Tutorial Abstracts) 2015: 5-6 - [c11]Matthew R. Gormley, Mo Yu, Mark Dredze:
Improved Relation Extraction with Feature-Rich Compositional Embedding Models. EMNLP 2015: 1774-1784 - [c10]Nanyun Peng, Francis Ferraro, Mo Yu, Nicholas Andrews, Jay DeYoung, Max Thomas, Matthew R. Gormley, Travis Wolfe, Craig Harman, Benjamin Van Durme, Mark Dredze:
A Concrete Chinese NLP Pipeline. HLT-NAACL 2015: 86-90 - [c9]Mo Yu, Matthew R. Gormley, Mark Dredze:
Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction. HLT-NAACL 2015: 1374-1379 - [i2]Matthew R. Gormley, Mo Yu, Mark Dredze:
Improved Relation Extraction with Feature-rich Compositional Embedding Models. CoRR abs/1505.02419 (2015) - [i1]Matthew R. Gormley, Mark Dredze, Jason Eisner:
Approximation-Aware Dependency Parsing by Belief Propagation. CoRR abs/1508.02375 (2015) - 2014
- [c8]Matthew R. Gormley, Jason Eisner:
Structured Belief Propagation for NLP. ACL (Tutorial Abstracts) 2014: 9-10 - [c7]Matthew R. Gormley, Margaret Mitchell, Benjamin Van Durme, Mark Dredze:
Low-Resource Semantic Role Labeling. ACL (1) 2014: 1177-1187 - 2013
- [c6]Matthew R. Gormley, Jason Eisner:
Nonconvex Global Optimization for Latent-Variable Models. ACL (1) 2013: 444-454 - [c5]Justin Snyder, Rebecca Knowles, Mark Dredze, Matthew R. Gormley, Travis Wolfe:
Topic Models and Metadata for Visualizing Text Corpora. HLT-NAACL 2013: 5-9 - 2012
- [c4]Spence Green, Nicholas Andrews, Matthew R. Gormley, Mark Dredze, Christopher D. Manning:
Entity Clustering Across Languages. HLT-NAACL 2012: 60-69 - [c3]Courtney Napoles, Matthew R. Gormley, Benjamin Van Durme:
Annotated Gigaword. AKBC-WEKEX@NAACL-HLT 2012: 95-100 - [c2]Matthew R. Gormley, Mark Dredze, Benjamin Van Durme, Jason Eisner:
Shared Components Topic Models. HLT-NAACL 2012: 783-792 - 2010
- [c1]Matthew R. Gormley, Adam Gerber, Mary P. Harper, Mark Dredze:
Non-Expert Correction of Automatically Generated Relation Annotations. Mturk@HLT-NAACL 2010: 204-207
Coauthor Index
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