activity
20242026
most citedUncertainty-aware Medical Diagnostic Phrase Identification and Grounding

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

astro-ph.IM2026

Earth Science Foundation Models: From Perception to Reasoning and Discovery

Xiangyu Zhao, Bo Liu, Yuehan Zhang +9

Large foundation models (FMs) are transforming Earth science by integrating heterogeneous multimodal data, such as multi-platform imagery, gridded reanalysis data, diverse geophysi…

cs.CV2026

SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture

Haiwen Diao, Penghao Wu, Hanming Deng +55

Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fra…

cs.CV2025★ 1 cited

GEMeX-RMCoT: An Enhanced Med-VQA Dataset for Region-Aware Multimodal Chain-of-Thought Reasoning

Bo Liu, Xiangyu Zhao, Along He +3

Medical visual question answering aims to support clinical decision-making by enabling models to answer natural language questions based on medical images. While recent advances in…

cs.AI2025

MSEarth: A Multimodal Benchmark for Earth Science Phenomenon Discovery with MLLMs

Xiangyu Zhao, Wanghan Xu, Bo Liu +7

The rapid advancement of multimodal large language models (MLLMs) offers new opportunities for complex scientific challenges, yet their application in earth science-especially at t…

cs.CV2024★ 2 cited

Uncertainty-aware Medical Diagnostic Phrase Identification and Grounding

Ke Zou, Yang Bai, Bo Liu +9

Medical phrase grounding is crucial for identifying relevant regions in medical images based on phrase queries, facilitating accurate image analysis and diagnosis. However, current…