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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

LASQ: A Low-resource Aspect-based Sentiment Quadruple Extraction Dataset

Aizihaierjiang Yusufu, Jiang Liu, Kamran Aziz +5

In recent years, aspect-based sentiment analysis (ABSA) has made rapid progress and shown strong practical value. However, existing research and benchmarks are largely concentrated…

cs.CL2025

DALR: Dual-level Alignment Learning for Multimodal Sentence Representation Learning

Kang He, Yuzhe Ding, Haining Wang +3

Previous multimodal sentence representation learning methods have achieved impressive performance. However, most approaches focus on aligning images and text at a coarse level, fac…

cs.CL2025

Zero-Shot Conversational Stance Detection: Dataset and Approaches

Yuzhe Ding, Kang He, Bobo Li +5

Stance detection, which aims to identify public opinion towards specific targets using social media data, is an important yet challenging task. With the increasing number of online…