From Insights to Actions: The Impact of Interpretability and Analysis Research on NLP
M. Mosbach, {V. Gautam, T. Vergara-Browne}, D. Klakow, M. Geva. 2024.

Understanding "Democratization" in NLP and ML Research
{A. Subramonian, V. Gautam}, D. Klakow, Z. Talat. 2024.

Robust Pronoun Fidelity with English LLMs: Are they Reasoning, Repeating, or Just Biased?
V. Gautam, E. Bingert, D. Zhu, A. Lauscher, D. Klakow. 2024.


Stop! In the Name of Flaws: Disentangling Personal Names and Sociodemographic Attributes in NLP
V. Gautam, A. Subramonian, A. Lauscher, O. Keyes.
Workshop on Gender Bias in Natural Language Processing, 2024 (to appear).

The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis
M. Zhang, V. Gautam, M. Wang, J. O. Alabi, X. Shen, D. Klakow, M. Mosbach.
Findings of ACL, 2024 (to appear).

What explains the success of cross-modal fine-tuning with ORCA?
{P. GarcĂ­a-de-Herreros, V. Gautam}, P. Slusallek, D. Klakow, M.Mosbach.
Workshop on Insights from Negative Results in NLP, 2024.

A Lightweight Method to Generate Unanswerable Questions in English
V. Gautam, M. Zhang, and D. Klakow.
Findings of EMNLP, 2023.

Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairness
A. Ovalle, A. Subramonian, V. Gautam, G. Gee, and K-W Chang.
AIES, 2023.

Avengers, Ensemble! Benefits of ensembling in grapheme-to-phoneme prediction
V. Gautam, W. Y. Li, Z. Mahmood, F. Mailhot, S. Nadig, R. Wang, and N. Zhang.

The Gender Gap Tracker: Using Natural Language Processing to measure gender bias in media
F. T. Asr, M. Mazraeh, A. Lopes, V. Gautam, J. Gonzales, P. Rao, and M. Taboada.
PLoS ONE, 2021.

Where I've worked