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20222026
most citedRevisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition

17 citations · 22 across the 21 of their papers we have counts for

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26 papers · 1 filter

cs.CL2026

ReCite: Agentic Reasoning for Faithful Citation

Yuyang Huang, Bobo Li, Jiajia Song +4

Accurate citations are the foundation of academic writing, tracing intellectual origins and substantiating core claims. However, manually navigating the growing volume of scientifi…

cs.CL2026

MMDS-Bench: Benchmarking Multimodal Large Language Models on Dynamic Stance in Social Media Interactions

Yuzhe Ding, Kang He, Li Zheng +5

Dynamic stance classification models how a reply responds to its direct parent message, rather than how a post relates to a fixed topic. Existing work has mainly studied this probl…

cs.CL2026

Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering

Li Zheng, Xin Zhang, Shuyi He +5

Accurate comprehension and controllable generation of emotion and rhetoric are pivotal for enhancing the reasoning capabilities of large language models (LLMs). Existing studies mo…

cs.CL2026

Enhance-then-Balance Modality Collaboration for Robust Multimodal Sentiment Analysis

Kang He, Yuzhe Ding, Xinrong Wang +3

Multimodal sentiment analysis (MSA) integrates heterogeneous text, audio, and visual signals to infer human emotions. While recent approaches leverage cross-modal complementarity,…

cs.CL2026

Dynamic Emotion and Personality Profiling for Multimodal Deception Detection

Li Zheng, Yanyi Luo, Hao Fei +5

Deception detection is of great significance for ensuring information security and conducting public opinion analysis, with personality factors and emotion cues playing a critical…

cs.CL2026

Code-MIE: A Code-style Model for Multimodal Information Extraction with Scene Graph and Entity Attribute Knowledge Enhancement

Jiang Liu, Ge Qiu, Hao Fei +5

With the rapid development of large language models (LLMs), more and more researchers have paid attention to information extraction based on LLMs. However, there are still some spa…