3 citations · 3 across the 7 of their papers we have counts for
8 papers
ProtoPur: Prototype-Purity Pseudo-Labeling for Weakly Supervised Instance Learning in Pathology
Chen Shu, Chengyang Zhang, Boyu Fu +5
Weak bag-level labels are widely available in computational pathology, whereas reliable instance-level annotations for whole-slide images remain expensive and ambiguous. Weakly sup…
Do Pathology Vision-Language Models Truly See Pathology?
Chengyang Zhang, Wenchuan Zhang, Bo Li +10
Pathology vision-language models (VLMs) have recently progressed rapidly and are commonly evaluated by answer accuracy on pathology VQA benchmarks. However, we dig into current eva…
PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow
Chengyang Zhang, Wenchuan Zhang, Bo Li +5
Recent advances in Multimodal Large Language Models (MLLMs) and agent workflows have shown strong promise for computational pathology, yet reliable patch-level reasoning remains ch…
CellScientist: From Execution Feedback to Auditable Model-Revision Trajectories for Cellular Perturbation Prediction
Mengran Li, Bo Li, Jiaying Wang +13
Cellular perturbation-response modeling requires coordinated choices of representations, fusion mechanisms, objectives, and training procedures. Large language models (LLMs) can pr…
PhenoProfiler: Advancing Phenotypic Learning for Image-based Drug Discovery
Bo Li, Bob Zhang, Chengyang Zhang +7
In the field of image-based drug discovery, capturing the phenotypic response of cells to various drug treatments and perturbations is a crucial step. However, existing methods req…
BjTT: A Large-scale Multimodal Dataset for Traffic Prediction
Chengyang Zhang, Yong Zhang, Qitan Shao +5
Traffic prediction is one of the most significant foundations in Intelligent Transportation Systems (ITS). Traditional traffic prediction methods rely only on historical traffic da…
Few-shot Object Localization
Yunhan Ren, Bo Li, Chengyang Zhang +2
Existing object localization methods are tailored to locate specific classes of objects, relying heavily on abundant labeled data for model optimization. However, acquiring large a…
ChatTraffic: Text-to-Traffic Generation via Diffusion Model
Chengyang Zhang, Yong Zhang, Qitan Shao +4
Traffic prediction is one of the most significant foundations in Intelligent Transportation Systems (ITS). Traditional traffic prediction methods rely only on historical traffic da…