{"slug": "atmoserc-modeling-dialogue-level-affective-atmosphere-for-emotion-recognition-in", "title": "AtmosERC: Modeling Dialogue-Level Affective Atmosphere for Emotion Recognition in Conversation", "summary": "Researchers propose AtmosERC, a graph-based framework for Emotion Recognition in Conversation (ERC) that models dialogue-level affective atmosphere to improve emotion prediction. The framework uses a relation-aware graph extractor to produce affective priors, enhancing both lightweight and LLM-based ERC systems, as demonstrated on four benchmarks.", "body_md": "arXiv:2607.26726v1 Announce Type: new\nAbstract: Emotion Recognition in Conversation (ERC) aims to predict utterance-level emotions in dialogues and has largely advanced through context-centric modeling. However, global context is a heterogeneous signal, and not all contextual information is equally relevant to emotion prediction. This paper focuses on the affect-oriented component of this signal, termed dialogue-level affective atmosphere, which captures a latent tendency commonly reflected in conversational emotion patterns. To estimate and exploit this tendency, we propose AtmosERC, a graph-based ERC framework that models each dialogue as a conversational graph over utterances and speakers. A relation-aware graph extractor filters and fuses heterogeneous graph signals to produce dialogue-level and speaker-conditioned affective priors. The resulting compact prior guides lightweight sequential emotion prediction and can also be verbalized into prompt-level cues for LLM-based ERC without modifying backbone models. Experiments on four ERC benchmarks show that AtmosERC improves lightweight ERC, enhances LLM-based ERC as a plug-in cue, and yields more stable predictions under local emotional deviations.", "url": "https://wpnews.pro/news/atmoserc-modeling-dialogue-level-affective-atmosphere-for-emotion-recognition-in", "canonical_source": "https://www.machinebrief.com/news/atmoserc-modeling-dialogue-level-affective-atmosphere-for-em-nm0k", "published_at": "2026-07-30 04:00:00+00:00", "updated_at": "2026-07-30 04:33:22.935748+00:00", "lang": "en", "topics": ["artificial-intelligence", "natural-language-processing", "machine-learning"], "entities": ["AtmosERC"], "alternates": {"html": "https://wpnews.pro/news/atmoserc-modeling-dialogue-level-affective-atmosphere-for-emotion-recognition-in", "markdown": "https://wpnews.pro/news/atmoserc-modeling-dialogue-level-affective-atmosphere-for-emotion-recognition-in.md", "text": "https://wpnews.pro/news/atmoserc-modeling-dialogue-level-affective-atmosphere-for-emotion-recognition-in.txt", "jsonld": "https://wpnews.pro/news/atmoserc-modeling-dialogue-level-affective-atmosphere-for-emotion-recognition-in.jsonld"}}