FakeReasoning is an MLLM-based framework for unified forgery detection and reasoning on AI-generated images, supported by the new MMFR-Dataset of 120K images and 378K annotations across 10 generators.
Visual instruction tuning,
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UniEmo unifies emotional understanding and generation by extracting multi-scale features via learnable expert queries, guiding diffusion-based image generation, and using dual feedback to improve both tasks.
AutoSpatial improves VLM spatial reasoning for social navigation by combining minimal manual supervision with auto-labeled VQA pairs and hierarchical training, showing gains up to 20.5% in action prediction over baselines.
Survey organizing multimodal affective computing research around four NLP tasks, method paradigms, datasets, evaluation protocols, and future directions while releasing a resource repository.
citing papers explorer
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Toward Generalizable Forgery Detection and Reasoning
FakeReasoning is an MLLM-based framework for unified forgery detection and reasoning on AI-generated images, supported by the new MMFR-Dataset of 120K images and 378K annotations across 10 generators.
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UniEmo: Unifying Emotional Understanding and Generation with Learnable Expert Queries
UniEmo unifies emotional understanding and generation by extracting multi-scale features via learnable expert queries, guiding diffusion-based image generation, and using dual feedback to improve both tasks.
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AutoSpatial: Visual-Language Reasoning for Social Robot Navigation through Efficient Spatial Reasoning Learning
AutoSpatial improves VLM spatial reasoning for social navigation by combining minimal manual supervision with auto-labeled VQA pairs and hierarchical training, showing gains up to 20.5% in action prediction over baselines.
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Recent Advances in Multimodal Affective Computing: An NLP Perspective
Survey organizing multimodal affective computing research around four NLP tasks, method paradigms, datasets, evaluation protocols, and future directions while releasing a resource repository.