Apoorva Nitsure

According to our database, Apoorva Nitsure authored at least 11 papers between 2023 and 2025.

Collaborative distances:

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

2025

Revisiting Group Relative Policy Optimization: Insights into On-Policy and Off-Policy Training.

Youssef Mroueh, Nicolas Dupuis, Brian Belgodere, Apoorva Nitsure, Mattia Rigotti, Kristjan H. Greenewald, Jirí Navrátil, Jerret Ross, Jesus Rios

CoRR, May, 2025

Information Theoretic Guarantees For Policy Alignment In Large Language Models.

Youssef Mroueh, Apoorva Nitsure

Trans. Mach. Learn. Res., 2025

2024

Auditing and Generating Synthetic Data With Controllable Trust Trade-Offs.

Brian Belgodere, Pierre L. Dognin, Adam Ivankay, Igor Melnyk, Youssef Mroueh, Aleksandra Mojsilovic, Jirí Navrátil, Apoorva Nitsure, Inkit Padhi, Mattia Rigotti, Jerret Ross, Yair Schiff, Radhika Vedpathak, Richard A. Young

IEEE J. Emerg. Sel. Topics Circuits Syst., December, 2024

Distributional Preference Alignment of LLMs via Optimal Transport.

Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jerret Ross

CoRR, 2024

VHDL-Eval: A Framework for Evaluating Large Language Models in VHDL Code Generation.

Prashanth Vijayaraghavan, Luyao Shi, Stefano Ambrogio, Charles Mackin, Apoorva Nitsure, David Beymer, Ehsan Degan

CoRR, 2024

Multivariate Stochastic Dominance via Optimal Transport and Applications to Models Benchmarking.

Gabriel Rioux, Apoorva Nitsure, Mattia Rigotti, Kristjan H. Greenewald, Youssef Mroueh

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Distributional Preference Alignment of LLMs via Optimal Transport.

Igor Melnyk, Youssef Mroueh, Brian Belgodere, Mattia Rigotti, Apoorva Nitsure, Mikhail Yurochkin, Kristjan H. Greenewald, Jirí Navrátil, Jarret Ross

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Chain-of-Descriptions: Improving Code LLMs for VHDL Code Generation and Summarization.

Prashanth Vijayaraghavan, Apoorva Nitsure, Charles Mackin, Luyao Shi, Stefano Ambrogio, Arvind Haran, Viresh Paruthi, Ali El-Zein, Dan Coops, David Beymer, Tyler Baldwin, Ehsan Degan

Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD, 2024

Risk Aware Benchmarking of Large Language Models.

Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jarret Ross

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Risk Assessment and Statistical Significance in the Age of Foundation Models.

Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti, Kristjan H. Greenewald, Brian Belgodere, Mikhail Yurochkin, Jirí Navrátil, Igor Melnyk, Jerret Ross

CoRR, 2023

A Scalable Space-efficient In-database Interpretability Framework for Embedding-based Semantic SQL Queries.

Prabhakar Kudva, Rajesh Bordawekar, Apoorva Nitsure

CoRR, 2023