LG-GER: Language-Guided Group Emotion Recognition via Multimodal Evidence Distillation
LG-GER is proposed, a language-guided distillation framework that uses a multimodal large language model (MLLM) to generate dense, spatially grounded evidence that achieves competitive or superior results compared to state-of-the-art methods that require detection and multi-stream processing at inference.