ActFER reformulates facial expression recognition as active tool-augmented visual reasoning with a custom reinforcement learning algorithm UC-GRPO that outperforms passive MLLM baselines on AU prediction.
arXiv:2511.00389
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The paper creates InsightVQA, a 725K QA-pair benchmark with perception, grounded-understanding, and cognition levels for emotion-cognitive visual question answering, plus a 30K-sample evaluation set and InsightNet baseline.
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ActFER: Agentic Facial Expression Recognition via Active Tool-Augmented Visual Reasoning
ActFER reformulates facial expression recognition as active tool-augmented visual reasoning with a custom reinforcement learning algorithm UC-GRPO that outperforms passive MLLM baselines on AU prediction.
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InsightVQA: High-Dimensional Emotion-Cognitive Visual Question Answering Benchmark
The paper creates InsightVQA, a 725K QA-pair benchmark with perception, grounded-understanding, and cognition levels for emotion-cognitive visual question answering, plus a 30K-sample evaluation set and InsightNet baseline.