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20232026
most citedVisual Large Language Models for Generalized and Specialized Applications

4 citations · 4 across the 6 of their papers we have counts for

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7 papers · 1 filter

cs.CV2026

ViT-AdaLA: Adapting Vision Transformers with Linear Attention

Yifan Li, Seunghyun Yoon, Viet Dac Lai +4

Vision Transformers (ViTs) based vision foundation models (VFMs) have achieved remarkable performance across diverse vision tasks, but suffer from quadratic complexity that limits…

cs.CV2025

Open Set Face Forgery Detection via Dual-Level Evidence Collection

Zhongyi Cai, Bryce Gernon, Wentao Bao +3

The surge in face forgeries has increasingly undermined confidence in the authenticity of online content. As generation algorithms rapidly evolve, new fake categories will constant…

cs.CV2025

ViT-Split: Unleashing the Power of Vision Foundation Models via Efficient Splitting Heads

Yifan Li, Xin Li, Tianqin Li +3

Vision foundation models (VFMs) have demonstrated remarkable performance across a wide range of downstream tasks. While several VFM adapters have shown promising results by leverag…

cs.CV2025

IndustryEQA: Pushing the Frontiers of Embodied Question Answering in Industrial Scenarios

Yifan Li, Yuhang Chen, Anh Dao +5

Existing Embodied Question Answering (EQA) benchmarks primarily focus on household environments, often overlooking safety-critical aspects and reasoning processes pertinent to indu…

cs.CV2025

Window Token Concatenation for Efficient Visual Large Language Models

Yifan Li, Wentao Bao, Botao Ye +4

To effectively reduce the visual tokens in Visual Large Language Models (VLLMs), we propose a novel approach called Window Token Concatenation (WiCo). Specifically, we employ a sli…

cs.CV20254 cited

Visual Large Language Models for Generalized and Specialized Applications

Yifan Li, Zhixin Lai, Wentao Bao +7

Visual-language models (VLM) have emerged as a powerful tool for learning a unified embedding space for vision and language. Inspired by large language models, which have demonstra…