Emma Strubell
Affiliations:- CMU, Pittsburgh, USA
- University of Massachusetts Amherst, USA
According to our database1,
Emma Strubell
authored at least 55 papers
between 2014 and 2024.
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Bibliography
2024
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.
CoRR, 2024
AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters.
CoRR, 2024
2023
J. Mach. Learn. Res., 2023
Queer People are People First: Deconstructing Sexual Identity Stereotypes in Large Language Models.
CoRR, 2023
Regularizing Self-training for Unsupervised Domain Adaptation via Structural Constraints.
CoRR, 2023
The Framework Tax: Disparities Between Inference Efficiency in Research and Deployment.
CoRR, 2023
On the Interactions of Structural Constraints and Data Resources for Structured Prediction.
Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Data-efficient Active Learning for Structured Prediction with Partial Annotation and Self-Training.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
To Build Our Future, We Must Know Our Past: Contextualizing Paradigm Shifts in Natural Language Processing.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Understanding the Effect of Model Compression on Social Bias in Large Language Models.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
The Framework Tax: Disparities Between Inference Efficiency in NLP Research and Deployment.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023
Annotating Mentions Alone Enables Efficient Domain Adaptation for Coreference Resolution.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
2022
Efficient and Equitable Natural Language Processing in the Age of Deep Learning (Dagstuhl Seminar 22232).
Dagstuhl Reports, 2022
Mention Annotations Alone Enable Efficient Domain Adaptation for Coreference Resolution.
CoRR, 2022
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Transfer Learning from Semantic Role Labeling to Event Argument Extraction with Template-based Slot Querying.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Train Flat, Then Compress: Sharpness-Aware Minimization Learns More Compressible Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022
Improving Compositional Generalization with Self-Training for Data-to-Text Generation.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
2021
Improving Compositional Generalization with Self-Training for Data-to-Text Generation.
CoRR, 2021
CoRR, 2021
On the Benefit of Syntactic Supervision for Cross-lingual Transfer in Semantic Role Labeling.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
Proceedings of the COMPASS '21: ACM SIGCAS Conference on Computing and Sustainable Societies, Virtual Event, Australia, 28 June 2021, 2021
Proceedings of the 5th Workshop on Structured Prediction for NLP, 2021
2020
J. Chem. Inf. Model., 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures.
Proceedings of the 13th Linguistic Annotation Workshop, 2019
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019
2018
Syntax Helps ELMo Understand Semantics: Is Syntax Still Relevant in a Deep Neural Architecture for SRL?
CoRR, 2018
Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
CoRR, 2017
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017
Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing, 2017
Attending to All Mention Pairs for Full Abstract Biological Relation Extraction.
Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017
2016
Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema.
Proceedings of the 2016 Text Analysis Conference, 2016
Proceedings of the NAACL HLT 2016, 2016
2015
Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches.
Proceedings of the 2015 Text Analysis Conference, 2015
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015
2014