SWIM aligns cross-attention maps from object nouns to ground-truth masks during training on the new NL-Refer dataset to enable text-only fine-grained video object understanding in MLLMs.
Fa- cial dynamics in video: Instruction tuning for improved fa- cial expression perception and contextual awareness
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
FaVChat proposes hierarchical prompt-query guided visual features and Data-Efficient GRPO for efficient training, plus the FaVChat-170K dataset, claiming consistent outperformance over prior VLLMs on facial video tasks.
LLaVA-Octopus introduces instruction-driven adaptive fusion of multiple visual projectors in a multimodal LLM to improve video understanding performance.
citing papers explorer
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See What I Mean: Aligning Vision and Language Representations for Video Fine-grained Object Understanding
SWIM aligns cross-attention maps from object nouns to ground-truth masks during training on the new NL-Refer dataset to enable text-only fine-grained video object understanding in MLLMs.
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FaVChat: Hierarchical Prompt-Query Guided Facial Video Understanding with Data-Efficient GRPO
FaVChat proposes hierarchical prompt-query guided visual features and Data-Efficient GRPO for efficient training, plus the FaVChat-170K dataset, claiming consistent outperformance over prior VLLMs on facial video tasks.
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LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding
LLaVA-Octopus introduces instruction-driven adaptive fusion of multiple visual projectors in a multimodal LLM to improve video understanding performance.