9 papers · 1 filter
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…
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,…
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…
TRIDENT: Enhancing Large Language Model Safety with Tri-Dimensional Diversified Red-Teaming Data Synthesis
Xiaorui Wu, Xiaofeng Mao, Fei Li +5
Large Language Models (LLMs) excel in various natural language processing tasks but remain vulnerable to generating harmful content or being exploited for malicious purposes. Altho…
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…
DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph Refinement
Shaoqing Lin, Chong Teng, Fei Li +3
Vision-Language Models (VLMs) generate discourse-level, multi-sentence visual descriptions, challenging text scene graph parsers built for single-sentence caption-to-graph mapping.…