Mahima Pushkarna

Orcid: 0000-0002-5903-5510

According to our database1, Mahima Pushkarna authored at least 13 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles.
Proceedings of the 29th International Conference on Intelligent User Interfaces, 2024

LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models.
Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024

Believing Anthropomorphism: Examining the Role of Anthropomorphic Cues on Trust in Large Language Models.
Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, 2024

2023
Investigating How Practitioners Use Human-AI Guidelines: A Case Study on the People + AI Guidebook.
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023

From Discovery to Adoption: Understanding the ML Practitioners' Interpretability Journey.
Proceedings of the 2023 ACM Designing Interactive Systems Conference, 2023

2022
GEMv2: Multilingual NLG Benchmarking in a Single Line of Code.
CoRR, 2022

Healthsheet: Development of a Transparency Artifact for Health Datasets.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI.
Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

LaMPost: Design and Evaluation of an AI-assisted Email Writing Prototype for Adults with Dyslexia.
Proceedings of the 24th International ACM SIGACCESS Conference on Computers and Accessibility, 2022

2020
The What-If Tool: Interactive Probing of Machine Learning Models.
IEEE Trans. Vis. Comput. Graph., 2020

Probing ML models for fairness with the what-if tool and SHAP: hands-on tutorial.
Proceedings of the FAT* '20: Conference on Fairness, 2020

The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 2020

2018
ClinicalVis: Supporting Clinical Task-Focused Design Evaluation.
CoRR, 2018


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