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20122026
most citedNetwork Sampling: From Static to Streaming Graphs

51 citations · 166 across the 80 of their papers we have counts for

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cs.CV2026

Attention-aware Inference Optimizations for Large Vision-Language Models with Memory-efficient Decoding

Fatih Ilhan, Gaowen Liu, Ramana Rao Kompella +5

Large Vision-Language Models (VLMs) have achieved remarkable success in multi-modal reasoning, but their inference time efficiency remains a significant challenge due to the memory…

cs.CV2026

A Multi-Agent Perception-Action Alliance for Efficient Long Video Reasoning

Yichang Xu, Gaowen Liu, Ramana Rao Kompella +6

This paper presents a multi-agent perception-action exploration alliance, dubbed A4VL, for efficient long-video reasoning. A4VL operates in a multi-round perception-action explorat…

cs.CV2026

Vision Verification Enhanced Fusion of VLMs for Efficient Visual Reasoning

Selim Furkan Tekin, Yichang Xu, Gaowen Liu +3

With the growing number and diversity of Vision-Language Models (VLMs), many works explore language-based ensemble, collaboration, and routing techniques across multiple VLMs to im…

cs.CV2026

Spectrally Distilled Representations Aligned with Instruction-Augmented LLMs for Satellite Imagery

Minh Kha Do, Wei Xiang, Kang Han +5

Vision-language foundation models (VLFMs) promise zero-shot and retrieval understanding for Earth observation. While operational satellite systems often lack full multi-spectral co…

cs.CV2026

GIFSplat: Generative Prior-Guided Iterative Feed-Forward 3D Gaussian Splatting from Sparse Views

Tianyu Chen, Wei Xiang, Kang Han +4

Feed-forward 3D reconstruction offers substantial runtime advantages over per-scene optimization, which remains slow at inference and often fragile under sparse views. However, exi…

cs.CV2026

SwiftNDC: Fast Neural Depth Correction for High-Fidelity 3D Reconstruction

Kang Han, Wei Xiang, Lu Yu +3

Depth-guided 3D reconstruction has gained popularity as a fast alternative to optimization-heavy approaches, yet existing methods still suffer from scale drift, multi-view inconsis…