3 accepted papers
Emotion recognition in conversation (ERC) is essential for dialogue systems to identify the emotions expressed by speakers. Although previous studies have made significant progress, accurate recognition and interpretation of similar fine-grained emotion properly accounting for individual variability…
Emotion Recognition in Conversation (ERC) aims to analyze the speaker’s emotional state in a conversation. Fully mining the information in multimodal and historical utterances plays a crucial role in the performance of the model. However, recent works in ERC focus on historical utterances modeling a…
Cross-lingual entity alignment (EA) is a critical step in the integration of multilingual knowledge, which aims to match entities with the same meaning in different knowledge graphs (KGs). Recently, based on GCN models and pre-trained language models (PLMs), EA has achieved breakthrough performance…