ClinicalVis: Supporting Clinical Task-Focused Design Evaluation. - Marzyeh Ghassemi; Mahima Pushkarna; James Wexler; Jesse Johnson; Paul Varghese (CoRR, 2018)

The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models. - Ian Tenney; James Wexler; Jasmijn Bastings; Tolga Bolukbasi; Andy Coenen; Sebastian Gehrmann; Ellen Jiang; Mahima Pushkarna; Carey Radebaugh; Emily Reif; Ann Yuan (EMNLP (Demos), 2020)

Probing ML models for fairness with the what-if tool and SHAP: hands-on tutorial. - James Wexler; Mahima Pushkarna; Sara Robinson; Tolga Bolukbasi; Andrew Zaldivar (FAT*, 2020)

The What-If Tool: Interactive Probing of Machine Learning Models. - James Wexler; Mahima Pushkarna; Tolga Bolukbasi; Martin Wattenberg; Fernanda B. Viégas; Jimbo Wilson (IEEE Trans. Vis. Comput. Graph., 2020)

LaMPost: Design and Evaluation of an AI-assisted Email Writing Prototype for Adults with Dyslexia. - Steven M. Goodman; Erin Buehler; Patrick Clary; Andy Coenen; Aaron Donsbach; Tiffanie N. Horne; Michal Lahav; Robert MacDonald; Rain Breaw Michaels; Ajit Narayanan; Mahima Pushkarna; Joel Riley; et al. (ASSETS, 2022)

Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI. - Mahima Pushkarna; Andrew Zaldivar; Oddur Kjartansson (FAccT, 2022)

Healthsheet: Development of a Transparency Artifact for Health Datasets. - Negar Rostamzadeh; Diana Mincu; Subhrajit Roy; Andrew Smart; Lauren Wilcox; Mahima Pushkarna; Jessica Schrouff; Razvan Amironesei; Nyalleng Moorosi; Katherine A. Heller (FAccT, 2022)

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code. - Sebastian Gehrmann; Abhik Bhattacharjee; Abinaya Mahendiran; Alex Wang; Alexandros Papangelis; Aman Madaan; Angelina McMillan-Major; Anna Shvets; Ashish Upadhyay; Bingsheng Yao; Bryan Wilie; Chandra Bhagavatula; et al. (CoRR, 2022)

From Discovery to Adoption: Understanding the ML Practitioners' Interpretability Journey. - Narges Ashtari; Ryan Mullins; Crystal Qian; James Wexler; Ian Tenney; Mahima Pushkarna (Conference on Designing Interactive Systems, 2023)

Investigating How Practitioners Use Human-AI Guidelines: A Case Study on the People + AI Guidebook. - Nur Yildirim; Mahima Pushkarna; Nitesh Goyal; Martin Wattenberg; Fernanda B. Viégas (CHI, 2023)

Believing Anthropomorphism: Examining the Role of Anthropomorphic Cues on Trust in Large Language Models. - Michelle Cohn; Mahima Pushkarna; Gbolahan O. Olanubi; Joseph M. Moran; Daniel Padgett; Zion Mengesha; Courtney Heldreth (CHI Extended Abstracts, 2024)

LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models. - Minsuk Kahng; Ian Tenney; Mahima Pushkarna; Michael Xieyang Liu; James Wexler; Emily Reif; Krystal Kallarackal; Minsuk Chang; Michael Terry; Lucas Dixon (CHI Extended Abstracts, 2024)

ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles. - Savvas Petridis; Benjamin D. Wedin; James Wexler; Mahima Pushkarna; Aaron Donsbach; Nitesh Goyal; Carrie J. Cai; Michael Terry (IUI, 2024)

LaMPost: AI Writing Assistance for Adults with Dyslexia Using Large Language Models. - Steven M. Goodman; Erin Buehler; Patrick Clary; Andy Coenen; Aaron Donsbach; Tiffanie N. Horne; Michal Lahav; Robert MacDonald; Rain Breaw Michaels; Ajit Narayanan; Mahima Pushkarna; Joel Riley; et al. (Commun. ACM, 2024)

LLM Comparator: Interactive Analysis of Side-by-Side Evaluation of Large Language Models. - Minsuk Kahng; Ian Tenney; Mahima Pushkarna; Michael Xieyang Liu; James Wexler; Emily Reif; Krystal Kallarackal; Minsuk Chang; Michael Terry; Lucas Dixon (IEEE Trans. Vis. Comput. Graph., 2025)