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20242026
most citedDoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)

7 citations · 7 across the 10 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

FiberGeoText: A Vision-Language Model for Population- Level Organization of Superficial White Matter

Yuqian Chen, R. Jarrett Rushmore, Guikun Chen +5

The superficial white matter (SWM), a critical brain region for cognition across the lifespan and brain disease, contains abundant short-range association fibers whose organization…

q-bio.GN2026

Generalizable single-cell perturbation response prediction using energy-guided flow matching

Jianan Wei, Jiajun Hong, Guikun Chen +3

Predicting phenotypic and transcriptional responses to perturbations at single-cell resolution provides a powerful tool for probing biological systems. However, existing methods ty…

cs.CV2026

Hyperbolic Hierarchical Clustering for Visual Representation Learning

Jianan Wei, Guikun Chen, Zhiyuan Weng +3

We investigate the token mixer in vision backbones by revisiting clustering, one of the most classic approaches in machine learning. An effective token mixer is a fundamental compo…

cs.CV2026

CoVStream: Edge-Cloud Collaboration for Understanding of Long Video Streams

Xu Liu, Guikun Chen, Zihao Yan +2

Long, continuous video streams are an increasingly critical driver of multimedia intelligence. Existing efforts often handle long videos with a sample-encode-reason approach using…

eess.IV2026

Tractogram foundation model

Guikun Chen, Yuqian Chen, Yijie Li +5

Diffusion MRI (dMRI) tractography is the only noninvasive approach for mapping white-matter pathways in the living human brain. It represents each brain as a tractogram: a large, u…

cs.CV2026

SinkTrack: Attention Sink based Context Anchoring for Large Language Models

Xu Liu, Guikun Chen, Wenguan Wang

Large language models (LLMs) suffer from hallucination and context forgetting. Prior studies suggest that attention drift is a primary cause of these problems, where LLMs' focus sh…