Swabha Swayamdipta

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Soavtorji

Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligencePreverjeni e-poštni naslov na cs.washington.edu
Yejin ChoiStanford University / NVIDIAPreverjeni e-poštni naslov na stanford.edu
Chris DyerDeepMind, Carnegie MellonPreverjeni e-poštni naslov na google.com
Doug DowneyAllen Institute for AI and Northwestern UniversityPreverjeni e-poštni naslov na eecs.northwestern.edu
Chandra BhagavatulaAllen Institute for Artificial IntelligencePreverjeni e-poštni naslov na allenai.org
Suchin GururanganUniversity of WashingtonPreverjeni e-poštni naslov na cs.washington.edu
Roy SchwartzAssociate Professor, the School of Computer Science, the Hebrew University of JerusalemPreverjeni e-poštni naslov na mail.huji.ac.il
Matthew E PetersSpiffy AI, Allen Institute for Artificial IntelligencePreverjeni e-poštni naslov na allenai.org
Alisa LiuUniversity of WashingtonPreverjeni e-poštni naslov na cs.washington.edu
Maarten SapCarnegie Mellon UniversityPreverjeni e-poštni naslov na cmu.edu
Rowan Zellersthinking machinesPreverjeni e-poštni naslov na cs.washington.edu
Iz BeltagyAllen Institute for Artificial IntelligencePreverjeni e-poštni naslov na beltagy.net
Kyle LoAllen Institute for Artificial IntelligencePreverjeni e-poštni naslov na allenai.org
Ana MarasovićUniversity of UtahPreverjeni e-poštni naslov na utah.edu
Ximing LuUniversity of WashingtonPreverjeni e-poštni naslov na cs.washington.edu
Zaid HarchaouiUniversity of WashingtonPreverjeni e-poštni naslov na uw.edu
John ThickstunAssistant Professor, Cornell UniversityPreverjeni e-poštni naslov na cornell.edu
Sam ThomsonMicrosoftPreverjeni e-poštni naslov na microsoft.com
Ronan Le BrasAllen Institute for Artificial IntelligencePreverjeni e-poštni naslov na allenai.org
Thomas WolfCo-founder at HuggingFacePreverjeni e-poštni naslov na polytechnique.edu

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Swabha Swayamdipta

University of Southern California

Preverjeni e-poštni naslov na usc.edu - Domača stran

Natural Language Processing Machine Learning


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
Don't Stop Pretraining: Adapt Language Models to Domains and Tasks S Gururangan, A Marasović, S Swayamdipta, K Lo, I Beltagy, D Downey, ... Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020	2561	2020
Annotation Artifacts in Natural Language Inference Data S Gururangan, S Swayamdipta, O Levy, R Schwartz, SR Bowman, ... Proceedings of the 2016 Conference of the North American Chapter of the …, 2018	1297	2018
Transfer Learning in Natural Language Processing S Ruder, ME Peters, S Swayamdipta, T Wolf Proceedings of the 2019 conference of the North American chapter of the …, 2019	840	2019
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics S Swayamdipta, R Schwartz, N Lourie, Y Wang, H Hajishirzi, NA Smith, ... Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020	435	2020
DExperts: Decoding-time controlled text generation with experts and anti-experts A Liu, M Sap, X Lu, S Swayamdipta, C Bhagavatula, NA Smith, Y Choi Proceedings of the 59th Annual Meeting of the Association for Computational …, 2021	366	2021
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers K Pillutla, S Swayamdipta, R Zellers, J Thickstun, S Welleck, Y Choi, ... Advances in Neural Information Processing Systems 34, 4816-4828, 2021	346	2021
A Dependency Parser for Tweets L Kong, N Schneider, S Swayamdipta, A Bhatia, C Dyer, NA Smith Proceedings of the 2014 Conference on Empirical Methods in Natural Language …, 2014	297	2014
DyNet: The Dynamic Neural Network Toolkit G Neubig, C Dyer, Y Goldberg, A Matthews, W Ammar, A Anastasopoulos, ... arXiv preprint arXiv:1701.03980, 2017	277	2017
Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection M Sap, S Swayamdipta, L Vianna, X Zhou, Y Choi, NA Smith Proceedings of the 2022 Conference of the North American Chapter of the …, 2021	266	2021
Understanding Dataset Difficulty with V-Usable Information. K Ethayarajh, Y Choi, S Swayamdipta International Conference on Machine Learning, 5988-6008, 2022	252	2022
Adversarial Filters of Dataset Biases R Le Bras, S Swayamdipta, C Bhagavatula, R Zellers, M Peters, ... Proceedings of ICML, 2019	241	2019
G-Daug: Generative Data Augmentation for Commonsense Reasoning Y Yang, C Malaviya, J Fernandez, S Swayamdipta, RL Bras, JP Wang, ... Findings of the Association for Computational Linguistics: EMNLP 2020, 1008 …, 2020	226*	2020
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation A Liu, S Swayamdipta, NA Smith, Y Choi Findings of the Association for Computational Linguistics: EMNLP 2022, 6826–6847, 2022	222	2022
Challenges in Automated Debiasing for Toxic Language Detection X Zhou, M Sap, S Swayamdipta, NA Smith, Y Choi Proceedings of 16th Conference of the European Chapter of the Association …, 2021	174	2021
The Right Tool for the Job: Matching Model and Instance Complexities R Schwartz, G Stanovsky, S Swayamdipta, J Dodge, NA Smith Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020	174	2020
Frame-Semantic Parsing with Softmax-Margin Segmental RNNs and a Syntactic Scaffold S Swayamdipta, S Thomson, C Dyer, NA Smith arXiv preprint arXiv:1706.09528, 2017	153	2017
Reframing Human-AI Collaboration for Generating Free-Text Explanations S Wiegreffe, J Hessel, S Swayamdipta, M Riedl, Y Choi Proceedings of the 2022 Conference of the North American Chapter of the …, 2021	150	2021
Syntactic Scaffolds for Semantic Structures S Swayamdipta, S Thomson, K Lee, L Zettlemoyer, C Dyer, NA Smith Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018	118	2018
Contrastive Explanations for Model Interpretability A Jacovi, S Swayamdipta, S Ravfogel, Y Elazar, Y Choi, Y Goldberg Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021	116	2021
We're afraid language models aren't modeling ambiguity A Liu, Z Wu, J Michael, A Suhr, P West, A Koller, S Swayamdipta, ... arXiv preprint arXiv:2304.14399, 2023	82	2023

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