Gagan Mundada — accepted AI-conference papers

2026

WS-GRPO: Weakly-Supervised Group-Relative Policy Optimization for Rollout-Efficient Reasoning

Gagan Mundada, Zihan Huang, Rohan Surana, Sheldon Yu, Jennifer Zhang, Xintong Li +5

ICML 2026poster

Group Relative Policy Optimization (GRPO) is effective for training language models on complex reasoning. However, since the objective is defined relative to a group of sampled trajectories, extended deliberation can create more chances to realize relative gains, leading to inefficient reasoning and…

Cited by 0 Source ↗Scholar ↗

2025

WildScore: Benchmarking MLLMs in-the-Wild Symbolic Music Reasoning

Gagan Mundada, Yash Vishe, Amit Namburi, Xin Xu, Zachary Novack, Julian McAuley +1

EMNLP 2025

Recent advances in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities across various vision-language tasks. However, their reasoning abilities in the multimodal symbolic music domain remain largely unexplored.We introduce WildScore, the first in-the-wild multimodal sy

Cited by 0 Source ↗PDF ↗code ↗Scholar ↗