most citedLong-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in Conversation

1 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Cross-Modal Emotion Understanding: A Transformer-GAT Approach for Dialogue Emotion Recognition

Jiaqi Qiao, Yifan Lyu, Xiujuan Xu

Multimodal emotion recognition is a key research area in affective computing, with applications in sentiment analysis, intelligent customer service, and human-computer interaction.…

cs.AI2026

SPAR-Hate: Auditor-Guided Multi-Perspective Role Reasoning for Bilingual Hate Speech Parsing

Yifan Lyu, Dianqing Lin, Xinran Li +2

Hate speech research has moved from coarse-grained classification towards structured parsing, where systems jointly identify targets, supporting arguments, and target-level labels.…

cs.AI2026

Signal or Spurious Cue? A Randomized Audit of Survey-Country Metadata in LLM Social Inference

Yifan Lyu, Xinran Li, Jiaqi Qiao +1

Survey-country metadata can improve an LLM's forecast of an individual response when informative, yet the same cue may redirect the forecast when assigned at random. A within-recor…

cs.CL2026

Expert-Guided Multimodal Fusion for Unified Emotion and Sentiment Analysis

Jiaqi Qiao, Xinran Li, Yifan Lyu +2

Multimodal emotion understanding requires the integration of heterogeneous data sources, including text, audio, and visual modalities, while simultaneously addressing discrete emot…

cs.AI2025★ 1 cited

Do LLMs Feel? Teaching Emotion Recognition with Prompts, Retrieval, and Curriculum Learning

Xinran Li, Yu Liu, Jiaqi Qiao +1

Emotion Recognition in Conversation (ERC) is a crucial task for understanding human emotions and enabling natural human-computer interaction. Although Large Language Models (LLMs)…

cs.LG2025★ 1 cited

Long-Short Distance Graph Neural Networks and Improved Curriculum Learning for Emotion Recognition in Conversation

Xinran Li, Xiujuan Xu, Jiaqi Qiao

Emotion Recognition in Conversation (ERC) is a practical and challenging task. This paper proposes a novel multimodal approach, the Long-Short Distance Graph Neural Network (LSDGNN…