Papers by Gagan Mundada
WildScore: Benchmarking MLLMs in-the-Wild Symbolic Music Reasoning (2025.emnlp-main)
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| Challenge: | Recent advances in Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities across various vision-language tasks. |
| Approach: | They propose a systematic taxonomy to evaluate MLLMs' ability to interpret real-world music scores and answer complex musicological queries. |
| Outcome: | The proposed model is based on real-world music scores and user-generated questions and discussions, and is scalable and controlled. |
Evaluating Language Model Pluralism through In-the-wild Crowd Discussions (2026.acl-long)
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Gagan Mundada, Rohan Surana, Nandhini Swaminathan, Bodhisattwa Prasad Majumder, Junda Wu, Julian McAuley, Zhouhang Xie
| Challenge: | Existing evaluation methods focus predominantly on multiple-choice and question-answering tasks, leaving open-ended generation largely unaddressed. |
| Approach: | They propose an evaluation framework that assesses LLM pluralism in open-ended generation by comparing outputs against free-form crowd responses. |
| Outcome: | The proposed evaluation framework decomposes ground-truth responses into atomic, non-overlapping claims and evaluates whether LLMs adequately cover this diverse claim space. |