Papers by Yimeng Sun

2 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.
OpenFraming: Open-sourced Tool for Computational Framing Analysis of Multilingual Data (2021.emnlp-demo)

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Challenge: Existing frameworks for analyzing frames in multilingual text documents are available online and via an API.
Approach: They propose a web-based system for analyzing frames in multilingual text documents . framework combines unsupervised and supervised machine learning and leverages a state-of-the-art multilingual language model .
Outcome: The proposed framework can significantly improve frame prediction performance while requiring a small sample of manual annotations.

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