7 citations · 7 across the 10 of their papers we have counts for
14 papers
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…
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…
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…
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…
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…
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…
SEED-GRPO: Semantic Entropy Enhanced GRPO for Uncertainty-Aware Policy Optimization
Minghan Chen, Guikun Chen, Wenguan Wang +1
Large language models (LLMs) exhibit varying levels of confidence across input prompts (questions): some lead to consistent, semantically similar answers, while others yield divers…
Do as We Do, Not as You Think: the Conformity of Large Language Models
Zhiyuan Weng, Guikun Chen, Wenguan Wang
Recent advancements in large language models (LLMs) revolutionize the field of intelligent agents, enabling collaborative multi-agent systems capable of tackling complex problems a…
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning
Guikun Chen, Xu Zhang, Xiaolin Hu +3
Chemical reaction data is a pivotal asset, driving advances in competitive fields such as pharmaceuticals, materials science, and industrial chemistry. Its proprietary nature rende…
Scene Graph Generation with Role-Playing Large Language Models
Guikun Chen, Jin Li, Wenguan Wang
Current approaches for open-vocabulary scene graph generation (OVSGG) use vision-language models such as CLIP and follow a standard zero-shot pipeline -- computing similarity betwe…
Hydra-SGG: Hybrid Relation Assignment for One-stage Scene Graph Generation
Minghan Chen, Guikun Chen, Wenguan Wang +1
DETR introduces a simplified one-stage framework for scene graph generation (SGG) but faces challenges of sparse supervision and false negative samples. The former occurs because e…
Neural Clustering based Visual Representation Learning
Guikun Chen, Xia Li, Yi Yang +1
We investigate a fundamental aspect of machine vision: the measurement of features, by revisiting clustering, one of the most classic approaches in machine learning and data analys…
DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)
Zongxin Yang, Guikun Chen, Xiaodi Li +2
Recent LLM-driven visual agents mainly focus on solving image-based tasks, which limits their ability to understand dynamic scenes, making it far from real-life applications like g…
A Survey on 3D Gaussian Splatting
Guikun Chen, Wenguan Wang
3D Gaussian splatting (GS) has emerged as a transformative technique in radiance fields. Unlike mainstream implicit neural models, 3D GS uses millions of learnable 3D Gaussians for…