Socratic Models compose zero-shot multimodal reasoning by prompting pretrained language and vision models to exchange information and enable new capabilities without finetuning.
Language models can see: Plugging visual controls in text generation
4 Pith papers cite this work. Polarity classification is still indexing.
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A single model trained only on image-text pairs gains instruction-following ability across images, video, and audio by routing all modalities through ImageBind's shared embedding space into Vicuna.
Mean-plus-trace alignment of text embeddings into the image distribution lets MLLM pretraining run on unpaired text, and the resulting text-only recipe (ReVision) scores 49.75 versus 48.91 for a 1M paired-image baseline.
A holistic survey of affective computing for intelligent agents covering emotion understanding via multimodal data, affective cognition, emotional expression synthesis, key challenges, and future directions emphasizing generative technologies.
citing papers explorer
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Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language
Socratic Models compose zero-shot multimodal reasoning by prompting pretrained language and vision models to exchange information and enable new capabilities without finetuning.
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PandaGPT: One Model To Instruction-Follow Them All
A single model trained only on image-text pairs gains instruction-following ability across images, video, and audio by routing all modalities through ImageBind's shared embedding space into Vicuna.
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Modality Gap-Driven Subspace Alignment Training Paradigm For Multimodal Large Language Models
Mean-plus-trace alignment of text embeddings into the image distribution lets MLLM pretraining run on unpaired text, and the resulting text-only recipe (ReVision) scores 49.75 versus 48.91 for a 1M paired-image baseline.
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Intelligent Agents with Emotional Intelligence: Current Trends, Challenges, and Future Prospects
A holistic survey of affective computing for intelligent agents covering emotion understanding via multimodal data, affective cognition, emotional expression synthesis, key challenges, and future directions emphasizing generative technologies.