Swayamdipta, Swabha

11 publications

ICLR 2026 Every Language Model Has a Forgery-Resistant Signature Matthew Finlayson, Xiang Ren, Swabha Swayamdipta

ICLR 2026 How Reliable Is Language Model Micro-Benchmarking? Gregory Yauney, Shahzaib Saqib Warraich, Swabha Swayamdipta

ICLR 2026 TrustGen: A Platform of Dynamic Benchmarking on the Trustworthiness of Generative Foundation Models Yue Huang, Chujie Gao, Siyuan Wu, Haoran Wang, Xiangqi Wang, Jiayi Ye, Yujun Zhou, Yanbo Wang, Jiawen Shi, Qihui Zhang, Han Bao, Zhaoyi Liu, Yuan Li, Tianrui Guan, Peiran Wang, Haomin Zhuang, Dongping Chen, Kehan Guo, Andy Zou, Bryan Hooi, Caiming Xiong, Elias Stengel-Eskin, Hongyang Zhang, Hongzhi Yin, Huan Zhang, Huaxiu Yao, Jieyu Zhang, Jaehong Yoon, Kai Shu, Ranjay Krishna, Swabha Swayamdipta, Weijia Shi, Xiang Li, Yuexing Hao, Zhihao Jia, Zhize Li, Xiuying Chen, Zhengzhong Tu, Xiyang Hu, Tianyi Zhou, Jieyu Zhao, Lichao Sun, Furong Huang, Or Cohen-Sasson, Prasanna Sattigeri, Anka Reuel, Max Lamparth, Yue Zhao, Nouha Dziri, Yu Su, Huan Sun, Heng Ji, Chaowei Xiao, Mohit Bansal, Nitesh V Chawla, Jian Pei, Jianfeng Gao, Michael Backes, Philip S. Yu, Neil Zhenqiang Gong, Pin-Yu Chen, Bo Li, Dawn Song, Xiangliang Zhang

NeurIPS 2025 Better Language Model Inversion by Compactly Representing Next-Token Distributions Murtaza Nazir, Matthew Finlayson, John Xavier Morris, Xiang Ren, Swabha Swayamdipta

ICLR 2024 Closing the Curious Case of Neural Text Degeneration Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal

JMLR 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, Zaid Harchaoui

NeurIPSW 2022 Information-Theoretic Evaluation of Free-Text Rationales with Conditional $\mathcal{V}$-Information Hanjie Chen, Faeze Brahman, Xiang Ren, Yangfeng Ji, Yejin Choi, Swabha Swayamdipta

ICML 2022 Understanding Dataset Difficulty with $\mathcal{V}$-Usable Information Kawin Ethayarajh, Yejin Choi, Swabha Swayamdipta

NeurIPS 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, Zaid Harchaoui

ICML 2020 Adversarial Filters of Dataset Biases Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew Peters, Ashish Sabharwal, Yejin Choi

ICLR 2018 Multi-Mention Learning for Reading Comprehension with Neural Cascades Swabha Swayamdipta, Ankur P. Parikh, Tom Kwiatkowski