33 citations · 36 across the 9 of their papers we have counts for
9 papers
Beyond Affinity: A Benchmark of 1D, 2D, and 3D Methods Reveals Critical Trade-offs in Structure-Based Drug Design
Kangyu Zheng, Kai Zhang, Jiale Tan +7
Currently, the field of structure-based drug design is dominated by three main types of algorithms: search-based algorithms, deep generative models, and reinforcement learning. Whi…
EditGRPO: Reinforcement Learning with Post-Rollout Edits for Clinically Accurate Chest X-Ray Report Generation
Kai Zhang, Christopher Malon, Lichao Sun +1
Radiology report generation requires advanced medical image analysis, effective temporal reasoning, and accurate text generation. Although recent innovations, particularly multimod…
RadAgents: Multimodal Agentic Reasoning for Chest X-ray Interpretation with Radiologist-like Workflows
Kai Zhang, Corey D Barrett, Jangwon Kim +3
Agentic systems offer a potential path to solve complex clinical tasks through collaboration among specialized agents, augmented by tool use and external knowledge bases. Neverthel…
Scaling Up Biomedical Vision-Language Models: Fine-Tuning, Instruction Tuning, and Multi-Modal Learning
Cheng Peng, Kai Zhang, Mengxian Lyu +3
To advance biomedical vison-language model capabilities through scaling up, fine-tuning, and instruction tuning, develop vision-language models with improved performance in handlin…
Unified-EGformer: Exposure Guided Lightweight Transformer for Mixed-Exposure Image Enhancement
Eashan Adhikarla, Kai Zhang, Rosaura G. VidalMata +5
Despite recent strides made by AI in image processing, the issue of mixed exposure, pivotal in many real-world scenarios like surveillance and photography, remains inadequately add…
Robust Computer Vision in an Ever-Changing World: A Survey of Techniques for Tackling Distribution Shifts
Eashan Adhikarla, Kai Zhang, Jun Yu +3
AI applications are becoming increasingly visible to the general public. There is a notable gap between the theoretical assumptions researchers make about computer vision models an…
TransMed: Large Language Models Enhance Vision Transformer for Biomedical Image Classification
Kaipeng Zheng, Weiran Huang, Lichao Sun
Few-shot learning has been studied to adapt models to tasks with very few samples. It holds profound significance, particularly in clinical tasks, due to the high annotation cost o…
Multimodal ChatGPT for Medical Applications: an Experimental Study of GPT-4V
Zhiling Yan, Kai Zhang, Rong Zhou +3
In this paper, we critically evaluate the capabilities of the state-of-the-art multimodal large language model, i.e., GPT-4 with Vision (GPT-4V), on Visual Question Answering (VQA)…
FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs
Shanshan Han, Baturalp Buyukates, Zijian Hu +13
This paper introduces FedSecurity, an end-to-end benchmark that serves as a supplementary component of the FedML library for simulating adversarial attacks and corresponding defens…