Annotation Artifacts in Natural Language Inference Data. - Suchin Gururangan; Swabha Swayamdipta; Omer Levy; Roy Schwartz 001; Samuel R. Bowman; Noah A. Smith (NAACL-HLT (2), 2018)

Variational Pretraining for Semi-supervised Text Classification. - Suchin Gururangan; Tam Dang; Dallas Card; Noah A. Smith (ACL (1), 2019)

Show Your Work: Improved Reporting of Experimental Results. - Jesse Dodge; Suchin Gururangan; Dallas Card; Roy Schwartz 001; Noah A. Smith (EMNLP/IJCNLP (1), 2019)

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 (ACL, 2020)

RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models. - Samuel Gehman; Suchin Gururangan; Maarten Sap; Yejin Choi 001; Noah A. Smith (EMNLP (Findings), 2020)

All That's 'Human' Is Not Gold: Evaluating Human Evaluation of Generated Text. - Elizabeth Clark; Tal August; Sofia Serrano; Nikita Haduong; Suchin Gururangan; Noah A. Smith (ACL/IJCNLP (1), 2021)

Expected Validation Performance and Estimation of a Random Variable's Maximum. - Jesse Dodge; Suchin Gururangan; Dallas Card; Roy Schwartz 001; Noah A. Smith (EMNLP (Findings), 2021)

Detoxifying Language Models Risks Marginalizing Minority Voices. - Albert Xu; Eshaan Pathak; Eric Wallace; Suchin Gururangan; Maarten Sap; Dan Klein 001 (NAACL-HLT, 2021)

Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection. - Suchin Gururangan; Dallas Card; Sarah K. Dreier; Emily K. Gade; Leroy Z. Wang; Zeyu Wang; Luke Zettlemoyer; Noah A. Smith (EMNLP, 2022)

M2D2: A Massively Multi-Domain Language Modeling Dataset. - Machel Reid; Victor Zhong; Suchin Gururangan; Luke Zettlemoyer (EMNLP, 2022)

Nearest Neighbor Zero-Shot Inference. - Weijia Shi; Julian Michael; Suchin Gururangan; Luke Zettlemoyer (EMNLP, 2022)

DEMix Layers: Disentangling Domains for Modular Language Modeling. - Suchin Gururangan; Mike Lewis; Ari Holtzman; Noah A. Smith; Luke Zettlemoyer (NAACL-HLT, 2022)

Time Waits for No One! Analysis and Challenges of Temporal Misalignment. - Kelvin Luu; Daniel Khashabi; Suchin Gururangan; Karishma Mandyam; Noah A. Smith (NAACL-HLT, 2022)

Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models. - Margaret Li; Suchin Gururangan; Tim Dettmers; Mike Lewis; Tim Althoff; Noah A. Smith; Luke Zettlemoyer (CoRR, 2022)

Editing Models with Task Arithmetic. - Gabriel Ilharco; Marco Túlio Ribeiro; Mitchell Wortsman; Suchin Gururangan; Ludwig Schmidt; Hannaneh Hajishirzi; Ali Farhadi (CoRR, 2022)

Scaling Expert Language Models with Unsupervised Domain Discovery. - Suchin Gururangan; Margaret Li; Mike Lewis; Weijia Shi; Tim Althoff; Noah A. Smith; Luke Zettlemoyer (CoRR, 2023)

SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. - Sewon Min; Suchin Gururangan; Eric Wallace; Hannaneh Hajishirzi; Noah A. Smith; Luke Zettlemoyer (CoRR, 2023)

lo-fi: distributed fine-tuning without communication. - Mitchell Wortsman; Suchin Gururangan; Shen Li; Ali Farhadi; Ludwig Schmidt; Michael G. Rabbat; Ari S. Morcos (Trans. Mach. Learn. Res., 2023)

AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters. - Li Lucy; Suchin Gururangan; Luca Soldaini; Emma Strubell; David Bamman; Lauren F. Klein; Jesse Dodge (ACL (1), 2024)

Time is Encoded in the Weights of Finetuned Language Models. - Kai Nylund; Suchin Gururangan; Noah A. Smith (ACL (1), 2024)

Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models. - Terra Blevins; Tomasz Limisiewicz; Suchin Gururangan; Margaret Li; Hila Gonen; Noah A. Smith; Luke Zettlemoyer (EMNLP, 2024)

SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. - Sewon Min; Suchin Gururangan; Eric Wallace; Weijia Shi; Hannaneh Hajishirzi; Noah A. Smith; Luke Zettlemoyer (ICLR, 2024)

LESS: Selecting Influential Data for Targeted Instruction Tuning. - Mengzhou Xia; Sadhika Malladi; Suchin Gururangan; Sanjeev Arora; Danqi Chen 001 (ICML, 2024)

DataComp-LM: In search of the next generation of training sets for language models. - Jeffrey Li; Alex Fang; Georgios Smyrnis; Maor Ivgi; Matt Jordan; Samir Yitzhak Gadre; Hritik Bansal; Etash Kumar Guha; Sedrick Scott Keh; Kushal Arora; Saurabh Garg; Rui Xin; et al. (NeurIPS, 2024)

Information Flow Control in Machine Learning through Modular Model Architecture. - Trishita Tiwari; Suchin Gururangan; Chuan Guo 001; Weizhe Hua; Sanjay Kariyappa; Udit Gupta; Wenjie Xiong 001; Kiwan Maeng; Hsien-Hsin S. Lee; G. Edward Suh (USENIX Security Symposium, 2024)

Language models scale reliably with over-training and on downstream tasks. - Samir Yitzhak Gadre; Georgios Smyrnis; Vaishaal Shankar; Suchin Gururangan; Mitchell Wortsman; Rulin Shao; Jean Mercat; Alex Fang; Jeffrey Li; Sedrick Keh; Rui Xin; Marianna Nezhurina; et al. (CoRR, 2024)

Data-Centric Methods for Decentralizing Large Language Models - Suchin Gururangan (2024)

Language models scale reliably with over-training and on downstream tasks. - Samir Yitzhak Gadre; Georgios Smyrnis; Vaishaal Shankar; Suchin Gururangan; Mitchell Wortsman; Rulin Shao; Jean Mercat; Alex Fang; Jeffrey Li; Sedrick Keh; Rui Xin; Marianna Nezhurina; et al. (ICLR, 2025)

Self-Generated Critiques Boost Reward Modeling for Language Models. - Yue Yu; Zhengxing Chen; Aston Zhang; Liang Tan; Chenguang Zhu 001; Richard Yuanzhe Pang; Yundi Qian; Xuewei Wang; Suchin Gururangan; Chao Zhang; Melanie Kambadur; Dhruv Mahajan 001; et al. (NAACL (Long Papers), 2025)

BTS: Harmonizing Specialized Experts into a Generalist LLM. - Qizhen Zhang 002; Prajjwal Bhargava; Chloe Bi; Chris X. Cai; Jakob N. Foerster; Jeremy Fu; Punit Singh Koura; Ruan Silva; Sheng Shen 016; Emily Dinan; Suchin Gururangan; Mike Lewis (CoRR, 2025)

Diversity-driven Data Selection for Language Model Tuning through Sparse Autoencoder. - Xianjun Yang; Shaoliang Nie; Lijuan Liu; Suchin Gururangan; Ujjwal Karn; Rui Hou; Madian Khabsa; Yuning Mao (CoRR, 2025)