Papers by Yueru Sun

1 papers
EmoMM: Benchmarking and Steering MLLM for Multimodal Emotion Recognition under Conflict and Missingness (2026.findings-acl)

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Challenge: Multimodal Large Language Models (MLLMs) have shown promise in MER, but their internal decision-making mechanisms under modality conflict and missingness remain underexplored.
Approach: They propose a multimodal large language model that can detect and control modality conflicts and missing subsets by a lightweight mechanism that detects and controls modality conflict.
Outcome: The proposed framework improves performance across settings, showing it can handle conflict and missing behaviors.

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