AsyMoE adds hyperbolic geometry for cross-modal hierarchies and evidence-priority experts to address vision-language asymmetry in LVLMs, reporting 1.5% average gains and 25.45% fewer active parameters.
arXiv:2401.17221
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The survey formalizes MLLM perception as a unified vision-language capability and traces its evolution via a new five-stage taxonomy while outlining future challenges.
EchoVLM, a mixture-of-experts vision-language model tailored to ultrasound, reports large improvements in report generation and diagnosis metrics over general VLMs, while underperforming on vascular data.
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Hyperbolic and Evidence-Prioritized Experts for Large Vision-Language Models
AsyMoE adds hyperbolic geometry for cross-modal hierarchies and evidence-priority experts to address vision-language asymmetry in LVLMs, reporting 1.5% average gains and 25.45% fewer active parameters.
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From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models
The survey formalizes MLLM perception as a unified vision-language capability and traces its evolution via a new five-stage taxonomy while outlining future challenges.
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EchoVLM: Dynamic Mixture-of-Experts Vision-Language Model for Universal Ultrasound Intelligence
EchoVLM, a mixture-of-experts vision-language model tailored to ultrasound, reports large improvements in report generation and diagnosis metrics over general VLMs, while underperforming on vascular data.