Vaishnavi Bhargava

According to our database, Vaishnavi Bhargava authored at least 9 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories.

Aditya Bharat Soni, Rajat Ghosh, Vaishnavi Bhargava, Valerie Chen, Debojyoti Dutta

CoRR, January, 2026

2025

Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go.

Yashshi Pipalani, Hritik Raj, Rajat Ghosh, Vaishnavi Bhargava, Debojyoti Dutta

CoRR, November, 2025

BAR Conjecture: the Feasibility of Inference Budget-Constrained LLM Services with Authenticity and Reasoning.

Jinan Zhou, Rajat Ghosh, Vaishnavi Bhargava, Debojyoti Dutta, Aryan Singhal

CoRR, July, 2025

Predictive Scaling Laws for Efficient GRPO Training of Large Reasoning Models.

Datta Nimmaturi, Vaishnavi Bhargava, Rajat Ghosh, Johnu George, Debojyoti Dutta

CoRR, July, 2025

2024

CPP-UT-Bench: Can LLMs Write Complex Unit Tests in C++?

Vaishnavi Bhargava, Rajat Ghosh, Debojyoti Dutta

CoRR, 2024

The ALCHEmist: Automated Labeling 500x CHEaper than LLM Data Annotators.

Tzu-Heng Huang, Catherine Cao, Vaishnavi Bhargava, Frederic Sala

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2022

s-LIME: Reconciling Locality and Fidelity in Linear Explanations.

Romaric Gaudel, Luis Galárraga, Julien Delaunay, Laurence Rozé, Vaishnavi Bhargava

Proceedings of the Advances in Intelligent Data Analysis XX, 2022

2020

LimeOut: An Ensemble Approach to Improve Process Fairness.

Vaishnavi Bhargava, Miguel Couceiro, Amedeo Napoli

Proceedings of the ECML PKDD 2020 Workshops, 2020

Making ML Models Fairer Through Explanations: The Case of LimeOut.

Guilherme Alves, Vaishnavi Bhargava, Miguel Couceiro, Amedeo Napoli

Proceedings of the Analysis of Images, Social Networks and Texts, 2020