Pick's Theorem via Minkowski's Theorem. - M. Ram Murty; Nithum Thain (Am. Math. Mon., 2007)

Computational Aspects of Multimarket Price Wars. - Nithum Thain; Adrian Vetta (WINE, 2009)

A Theoretical Examination of Practical Game Playing: Lookahead Search. - Vahab S. Mirrokni; Nithum Thain; Adrian Vetta (SAGT, 2012)

On the Implications of Lookahead Search in Game Playing - Vahab S. Mirrokni; Nithum Thain; Adrian Vetta (CoRR, 2012)

To Save Or Not To Save: The Fisher Game. - Ruta Mehta; Nithum Thain; László A. Végh; Adrian Vetta (WINE, 2014)

Ex Machina: Personal Attacks Seen at Scale. - Ellery Wulczyn; Nithum Thain; Lucas Dixon (WWW, 2017)

Conversations Gone Awry: Detecting Early Signs of Conversational Failure. - Justine Zhang; Jonathan P. Chang; Cristian Danescu-Niculescu-Mizil; Lucas Dixon; Yiqing Hua; Dario Taraborelli; Nithum Thain (ACL (1), 2018)

Measuring and Mitigating Unintended Bias in Text Classification. - Lucas Dixon; John Li; Jeffrey Sorensen; Nithum Thain; Lucy Vasserman (AIES, 2018)

WikiConv: A Corpus of the Complete Conversational History of a Large Online Collaborative Community. - Yiqing Hua; Cristian Danescu-Niculescu-Mizil; Dario Taraborelli; Nithum Thain; Jeffery Sorensen; Lucas Dixon (EMNLP, 2018)

ConvAI at SemEval-2019 Task 6: Offensive Language Identification and Categorization with Perspective and BERT. - John Pavlopoulos; Nithum Thain; Lucas Dixon; Ion Androutsopoulos (SemEval@NAACL-HLT, 2019)

Crowdsourcing Subjective Tasks: The Case Study of Understanding Toxicity in Online Discussions. - Lora Aroyo; Lucas Dixon; Nithum Thain; Olivia Redfield; Rachel Rosen (WWW (Companion Volume), 2019)

Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification. - Daniel Borkan; Lucas Dixon; Jeffrey Sorensen; Nithum Thain; Lucy Vasserman (WWW (Companion Volume), 2019)

Limitations of Pinned AUC for Measuring Unintended Bias. - Daniel Borkan; Lucas Dixon; John Li; Jeffrey Sorensen; Nithum Thain; Lucy Vasserman (CoRR, 2019)

Debiasing Embeddings for Reduced Gender Bias in Text Classification. - Flavien Prost; Nithum Thain; Tolga Bolukbasi (CoRR, 2019)

Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems. - Xuezhi Wang 002; Nithum Thain; Anu Sinha; Ed H. Chi; Jilin Chen; Alex Beutel (CoRR, 2019)

Six Attributes of Unhealthy Conversations. - Ilan Price; Jordan Gifford-Moore; Jory Flemming; Saul Musker; Maayan Roichman; Guillaume Sylvain; Nithum Thain; Lucas Dixon; Jeffrey Sorensen (WOAH, 2020)

Toxicity Detection: Does Context Really Matter? - John Pavlopoulos; Jeffrey Sorensen; Lucas Dixon; Nithum Thain; Ion Androutsopoulos (ACL, 2020)

Fairness without Demographics through Adversarially Reweighted Learning. - Preethi Lahoti; Alex Beutel; Jilin Chen; Kang Lee; Flavien Prost; Nithum Thain; Xuezhi Wang 002; Ed H. Chi (NeurIPS, 2020)

Six Attributes of Unhealthy Conversation. - Ilan Price; Jordan Gifford-Moore; Jory Flemming; Saul Musker; Maayan Roichman; Guillaume Sylvain; Nithum Thain; Lucas Dixon; Jeffrey Sorensen (CoRR, 2020)

Can We Improve Model Robustness through Secondary Attribute Counterfactuals? - Ananth Balashankar; Xuezhi Wang 002; Ben Packer; Nithum Thain; Ed H. Chi; Alex Beutel (EMNLP (1), 2021)

Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. - Xuezhi Wang 002; Nithum Thain; Anu Sinha; Flavien Prost; Ed H. Chi; Jilin Chen; Alex Beutel (WSDM, 2021)

Measuring Recommender System Effects with Simulated Users. - Sirui Yao; Yoni Halpern; Nithum Thain; Xuezhi Wang 002; Kang Lee; Flavien Prost; Ed H. Chi; Jilin Chen; Alex Beutel (CoRR, 2021)

Plex: Towards Reliability using Pretrained Large Model Extensions. - Dustin Tran; Jeremiah Z. Liu; Michael W. Dusenberry; Du Phan; Mark Collier; Jie Ren 006; Kehang Han; Zi Wang; Zelda Mariet; Huiyi Hu; Neil Band; Tim G. J. Rudner; et al. (CoRR, 2022)

Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. - Ananth Balashankar; Xuezhi Wang 002; Yao Qin 001; Ben Packer; Nithum Thain; Ed H. Chi; Jilin Chen; Alex Beutel (EMNLP (Findings), 2023)

Towards Agile Text Classifiers for Everyone. - Maximilian Mozes; Jessica Hoffmann; Katrin Tomanek; Muhamed Kouate; Nithum Thain; Ann Yuan; Tolga Bolukbasi; Lucas Dixon (EMNLP (Findings), 2023)

JUAGE at SemEval-2023 Task 10: Parameter Efficient Classification. - Jeffrey Sorensen; Katerina Korre; John Pavlopoulos; Katrin Tomanek; Nithum Thain; Lucas Dixon; Léo Laugier (SemEval@ACL, 2023)

Gradient-Based Automated Iterative Recovery for Parameter-Efficient Tuning. - Maximilian Mozes; Tolga Bolukbasi; Ann Yuan; Frederick Liu; Nithum Thain; Lucas Dixon (CoRR, 2023)

Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. - Ananth Balashankar; Xuezhi Wang 002; Yao Qin 001; Ben Packer; Nithum Thain; Jilin Chen; Ed H. Chi; Alex Beutel (CoRR, 2023)

Classifying constructive comments. - Varada Kolhatkar; Nithum Thain; Jeffrey Sorensen; Lucas Dixon; Maite Taboada (First Monday, 2023)

ConstitutionalExperts: Training a Mixture of Principle-based Prompts. - Savvas Petridis; Ben Wedin; Ann Yuan; James Wexler; Nithum Thain (ACL (Short Papers), 2024)

Detecting Hallucination and Coverage Errors in Retrieval Augmented Generation for Controversial Topics. - Tyler A. Chang; Katrin Tomanek; Jessica Hoffmann; Nithum Thain; Erin MacMurray van Liemt; Kathleen S. Meier-Hellstern; Lucas Dixon (LREC/COLING, 2024)

Thinking Like a Scientist: Can Interactive Simulations Foster Critical AI Literacy? - Yiling Zhao; Audrey L. Michal; Nithum Thain; Hari Subramonyam (AIED (2), 2025)

Improving Neutral Point of View Text Generation through Parameter-Efficient Reinforcement Learning and a Small-Scale High-Quality Dataset. - Jessica Hoffmann; Christiane Ahlheim; Zac Yu; Aria Walfrand; Jarvis Jin; Marie Tano; Ahmad Beirami; Erin van Liemt; Nithum Thain; Hakim Sidahmed; Lucas Dixon (CoRR, 2025)