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20242026
most citedERNIE 5.0 Technical Report

2 citations · 4 across the 9 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.CV2026

DK-VLM: Geometry as Position for Spatial Reasoning in Vision-Language Models

Han Su, Meng Tian, Tianyu Huang +7

Vision-language models still struggle to understand 3D spatial relations across views and update spatial judgments as the observer moves. A common approach fuses 3D reconstruction…

cs.CV2026

4D-WAM: 4D Consistent World Modeling for Autonomous Driving

Jiacheng Fu, Yibo Yuan, Meng Tian +8

Emerging World-Action Models (WAMs) have demonstrated promising performance in autonomous driving by jointly modeling future driving scene evolution and trajectory planning. Howeve…

cs.CV2026

SUV: Future Scene Understanding as Video Generation for End-to-End Driving

Yibo Yuan, Jiacheng Fu, Jiangtong Zhu +8

End-to-end driving requires a coherent understanding of future scenes, yet existing methods model these scenes using task-specific heads and output formats, with limited scalabilit…

cs.CL2026★ 2 cited

ERNIE 5.0 Technical Report

Haifeng Wang, Hua Wu, Tian Wu +432

In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio…

cs.CV2026

SkinFlow: Efficient Information Transmission for Open Dermatological Diagnosis via Dynamic Visual Encoding and Staged RL

Lijun Liu, Linwei Chen, Zhishou Zhang +7

General-purpose Large Vision-Language Models (LVLMs), despite their massive scale, often falter in dermatology due to "diffuse attention" - the inability to disentangle subtle path…