2 citations · 2 across the 6 of their papers we have counts for
6 papers
Generation or Judgement? A Paradigm Perspective on LLM-Based Emotion-Cause Pair Extraction in Conversation
Weijie Feng, Hongchuang Wang, Binbin Liu +1
Emotion-cause pair extraction in conversation (ECPEC) identifies utterance pairs in which one utterance causes an emotion expressed in another. Recent LLM-based approaches formulat…
AtmosERC: Modeling Dialogue-Level Affective Atmosphere for Emotion Recognition in Conversation
Weijie Feng, Tongwei Zhang, Binbin Liu +1
Emotion Recognition in Conversation (ERC) plays a key role in developing emotionally responsive conversational systems, and contextual modeling is central to this task. Several stu…
Emotion-Cause Pair Extraction in Conversations via Semantic Decoupling and Graph Alignment
Tianxiang Ma, Weijie Feng, Xinyu Wang +1
Emotion-Cause Pair Extraction in Conversations (ECPEC) aims to identify the set of causal relations between emotion utterances and their triggering causes within a dialogue. Most e…
SparkAlign: A Star-Hopping Heuristic for Efficient Unsupervised Plain Graph Alignment
Boyan Wang, Weijie Feng, Jinyang Huang +4
Unsupervised plain graph alignment (UPGA) seeks corresponding nodes between two graphs from topology alone, without attributes or seed anchors. The dominant embed-then-match paradi…
AMMSM: Adaptive Motion Magnification and Sparse Mamba for Micro-Expression Recognition
Xuxiong Liu, Tengteng Dong, Fei Wang +2
Micro-expressions are typically regarded as unconscious manifestations of a person's genuine emotions. However, their short duration and subtle signals pose significant challenges…
Compound Expression Recognition via Multi Model Ensemble for the ABAW7 Challenge
Xuxiong Liu, Kang Shen, Jun Yao +6
Compound Expression Recognition (CER) is vital for effective interpersonal interactions. Human emotional expressions are inherently complex due to the presence of compound expressi…