Swabha Swayamdipta

According to our database, Swabha Swayamdipta authored at least 53 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Political-LLM: Large Language Models in Political Science.

Lincan Li, Jiaqi Li, Catherine Chen, Fred Gui, Hongjia Yang, Chenxiao Yu, Zhengguang Wang, Jianing Cai, Junlong Aaron Zhou, Bolin Shen, Alex Qian, Weixin Chen, Zhongkai Xue, Lichao Sun, Lifang He, Hanjie Chen, Kaize Ding, Zijian Du, Fangzhou Mu, Jiaxin Pei, Jieyu Zhao, Swabha Swayamdipta, Willie Neiswanger, Hua Wei, Xiyang Hu, Shixiang Zhu, Tianlong Chen, Yingzhou Lu, Yang Shi, Lianhui Qin, Tianfan Fu, Zhengzhong Tu, Yuzhe Yang, Jaemin Yoo, Jiaheng Zhang, Ryan A. Rossi, Liang Zhan, Liang Zhao, Emilio Ferrara, Yan Liu, Furong Huang, Xiangliang Zhang, Lawrence Rothenberg, Shuiwang Ji, Philip S. Yu, Yue Zhao, Yushun Dong

CoRR, 2024

Crowd-Calibrator: Can Annotator Disagreement Inform Calibration in Subjective Tasks?

Urja Khurana, Eric T. Nalisnick, Antske Fokkens, Swabha Swayamdipta

CoRR, 2024

Logits of API-Protected LLMs Leak Proprietary Information.

Matthew Finlayson, Xiang Ren, Swabha Swayamdipta

CoRR, 2024

Generative Explanations for Program Synthesizers.

Amirmohammad Nazari, Souti Chattopadhyay, Swabha Swayamdipta, Mukund Raghothaman

CoRR, 2024

Generating Function Names to Improve Comprehension of Synthesized Programs.

Amirmohammad Nazari, Swabha Swayamdipta, Souti Chattopadhyay, Mukund Raghothaman

Proceedings of the 2024 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 2024

NeuroComparatives: Neuro-Symbolic Distillation of Comparative Knowledge.

Phillip Howard, Junlin Wang, Vasudev Lal, Gadi Singer, Yejin Choi, Swabha Swayamdipta

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

NomNom: Explanatory Function Names for Program Synthesizers.

Amirmohammad Nazari, Souti Chattopadhyay, Swabha Swayamdipta, Mukund Raghothaman

Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings, 2024

Closing the Curious Case of Neural Text Degeneration.

Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Does Video Summarization Require Videos? Quantifying the Effectiveness of Language in Video Summarization.

Yoonsoo Nam, Adam Lehavi, Daniel Yang, Digbalay Bose, Swabha Swayamdipta, Shrikanth Narayanan

Proceedings of the IEEE International Conference on Acoustics, 2024

OATH-Frames: Characterizing Online Attitudes Towards Homelessness with LLM Assistants.

Jaspreet Ranjit, Brihi Joshi, Rebecca Dorn, Laura Petry, Olga Koumoundouros, Jayne Bottarini, Peichen Liu, Eric Rice, Swabha Swayamdipta

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Out-of-Distribution Detection through Soft Clustering with Non-Negative Kernel Regression.

Aryan Gulati, Xingjian Dong, Carlos Hurtado, Sarath Shekkizhar, Swabha Swayamdipta, Antonio Ortega

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Compare without Despair: Reliable Preference Evaluation with Generation Separability.

Sayan Ghosh, Tejas Srinivasan, Swabha Swayamdipta

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Annotating FrameNet via Structure-Conditioned Language Generation.

Xinyue Cui, Swabha Swayamdipta

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, 2024

2023

MAUVE Scores for Generative Models: Theory and Practice.

Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui

J. Mach. Learn. Res., 2023

We're Afraid Language Models Aren't Modeling Ambiguity.

Alisa Liu, Zhaofeng Wu, Julian Michael, Alane Suhr, Peter West, Alexander Koller, Swabha Swayamdipta, Noah A. Smith, Yejin Choi

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statements.

Xuhui Zhou, Hao Zhu, Akhila Yerukola, Thomas Davidson, Jena D. Hwang, Swabha Swayamdipta, Maarten Sap

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

REV: Information-Theoretic Evaluation of Free-Text Rationales.

Hanjie Chen, Faeze Brahman, Xiang Ren, Yangfeng Ji, Yejin Choi, Swabha Swayamdipta

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation.

Chandra Bhagavatula, Jena D. Hwang, Doug Downey, Ronan Le Bras, Ximing Lu, Lianhui Qin, Keisuke Sakaguchi, Swabha Swayamdipta, Peter West, Yejin Choi

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

I2D2: Inductive Knowledge Distillation with NeuroLogic and Self-Imitation.

Chandra Bhagavatula, Jena D. Hwang, Doug Downey, Ronan Le Bras, Ximing Lu, Keisuke Sakaguchi, Swabha Swayamdipta, Peter West, Yejin Choi

CoRR, 2022

Reframing Human-AI Collaboration for Generating Free-Text Explanations.

Sarah Wiegreffe, Jack Hessel, Swabha Swayamdipta, Mark O. Riedl, Yejin Choi

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection.

Maarten Sap, Swabha Swayamdipta, Laura Vianna, Xuhui Zhou, Yejin Choi, Noah A. Smith

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Understanding Dataset Difficulty with <i>V</i>-Usable Information.

Kawin Ethayarajh, Yejin Choi, Swabha Swayamdipta

Proceedings of the International Conference on Machine Learning, 2022

Investigating the Benefits of Free-Form Rationales.

Jiao Sun, Swabha Swayamdipta, Jonathan May, Xuezhe Ma

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation.

Alisa Liu, Swabha Swayamdipta, Noah A. Smith, Yejin Choi

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

NeuroCounterfactuals: Beyond Minimal-Edit Counterfactuals for Richer Data Augmentation.

Phillip Howard, Gadi Singer, Vasudev Lal, Yejin Choi, Swabha Swayamdipta

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Information-Theoretic Measures of Dataset Difficulty.

Kawin Ethayarajh, Yejin Choi, Swabha Swayamdipta

CoRR, 2021

Sister Help: Data Augmentation for Frame-Semantic Role Labeling.

Ayush Pancholy, Miriam R. L. Petruck, Swabha Swayamdipta

CoRR, 2021

On-the-Fly Controlled Text Generation with Experts and Anti-Experts.

Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, Yejin Choi

CoRR, 2021

MAUVE: Human-Machine Divergence Curves for Evaluating Open-Ended Text Generation.

Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Yejin Choi, Zaïd Harchaoui

CoRR, 2021

MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers.

Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaïd Harchaoui

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Contrastive Explanations for Model Interpretability.

Alon Jacovi, Swabha Swayamdipta, Shauli Ravfogel, Yanai Elazar, Yejin Choi, Yoav Goldberg

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Challenges in Automated Debiasing for Toxic Language Detection.

Xuhui Zhou, Maarten Sap, Swabha Swayamdipta, Yejin Choi, Noah A. Smith

Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts.

Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, Yejin Choi

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

Adversarial Filters of Dataset Biases.

Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, Yejin Choi

Proceedings of the 37th International Conference on Machine Learning, 2020

G-DAug: Generative Data Augmentation for Commonsense Reasoning.

Yiben Yang, Chaitanya Malaviya, Jared Fernandez, Swabha Swayamdipta, Ronan Le Bras, Ji-Ping Wang, Chandra Bhagavatula, Yejin Choi, Doug Downey

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics.

Swabha Swayamdipta, Roy Schwartz, Nicholas Lourie, Yizhong Wang, Hannaneh Hajishirzi, Noah A. Smith, Yejin Choi

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

The Right Tool for the Job: Matching Model and Instance Complexities.

Roy Schwartz, Gabriel Stanovsky, Swabha Swayamdipta, Jesse Dodge, Noah A. Smith

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Don't Stop Pretraining: Adapt Language Models to Domains and Tasks.

Suchin Gururangan, Ana Marasovic, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, Noah A. Smith

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Shallow Syntax in Deep Water.

Swabha Swayamdipta, Matthew E. Peters, Brendan Roof, Chris Dyer, Noah A. Smith

CoRR, 2019

Transfer Learning in Natural Language Processing.

Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, Thomas Wolf

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

2018

Learning Joint Semantic Parsers from Disjoint Data.

Hao Peng, Sam Thomson, Swabha Swayamdipta, Noah A. Smith

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Annotation Artifacts in Natural Language Inference Data.

Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel R. Bowman, Noah A. Smith

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Multi-Mention Learning for Reading Comprehension with Neural Cascades.

Swabha Swayamdipta, Ankur P. Parikh, Tom Kwiatkowski

Proceedings of the 6th International Conference on Learning Representations, 2018

Syntactic Scaffolds for Semantic Structures.

Swabha Swayamdipta, Sam Thomson, Kenton Lee, Luke Zettlemoyer, Chris Dyer, Noah A. Smith

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Frame Semantics across Languages: Towards a Multilingual FrameNet.

Collin F. Baker, Michael Ellsworth, Miriam R. L. Petruck, Swabha Swayamdipta

Proceedings of the COLING 2018, 2018

Polyglot Semantic Role Labeling.

Phoebe Mulcaire, Swabha Swayamdipta, Noah A. Smith

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Frame-Semantic Parsing with Softmax-Margin Segmental RNNs and a Syntactic Scaffold.

Swabha Swayamdipta, Sam Thomson, Chris Dyer, Noah A. Smith

CoRR, 2017

DyNet: The Dynamic Neural Network Toolkit.

Graham Neubig, Chris Dyer, Yoav Goldberg, Austin Matthews, Waleed Ammar, Antonios Anastasopoulos, Miguel Ballesteros, David Chiang, Daniel Clothiaux, Trevor Cohn, Kevin Duh, Manaal Faruqui, Cynthia Gan, Dan Garrette, Yangfeng Ji, Lingpeng Kong, Adhiguna Kuncoro, Gaurav Kumar, Chaitanya Malaviya, Paul Michel, Yusuke Oda, Matthew Richardson, Naomi Saphra, Swabha Swayamdipta, Pengcheng Yin

CoRR, 2017

2016

Greedy, Joint Syntactic-Semantic Parsing with Stack LSTMs.

Swabha Swayamdipta, Miguel Ballesteros, Chris Dyer, Noah A. Smith

Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, 2016

2014

The CMU Machine Translation Systems at WMT 2014.

Austin Matthews, Waleed Ammar, Archna Bhatia, Weston Feely, Greg Hanneman, Eva Schlinger, Swabha Swayamdipta, Yulia Tsvetkov, Alon Lavie, Chris Dyer

Proceedings of the Ninth Workshop on Statistical Machine Translation, 2014

CMU: Arc-Factored, Discriminative Semantic Dependency Parsing.

Sam Thomson, Brendan O'Connor, Jeffrey Flanigan, David Bamman, Jesse Dodge, Swabha Swayamdipta, Nathan Schneider, Chris Dyer, Noah A. Smith

Proceedings of the 8th International Workshop on Semantic Evaluation, 2014

A Dependency Parser for Tweets.

Lingpeng Kong, Nathan Schneider, Swabha Swayamdipta, Archna Bhatia, Chris Dyer, Noah A. Smith

Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, 2014

2012

The Pursuit of Power and Its Manifestation in Written Dialog.

Swabha Swayamdipta, Owen Rambow

Proceedings of the Sixth IEEE International Conference on Semantic Computing, 2012