most citedPhenome-Wide Multi-Omics Integration Uncovers Distinct Archetypes of Human Aging

1 citations · 1 across the 10 of their papers we have counts for

collaborators

11 papers

cs.CV2026

Grounding Isn't Knowing: Do VLMs Need Object Localization for Spatial Reasoning?

Xiwei Liu, Yulong Li, Xinlin Zhuang +5

Vision-language models (VLMs) can answer spatial questions, yet the mechanisms connecting object grounding to spatial reasoning remain poorly understood. It is underexplored whethe…

cs.LG2026

AMO: Adaptive Muon Orthogonalization

Xinlin Zhuang, Panyi Ouyang, Yichen Li +7

Muon has recently emerged as a competitive alternative to AdamW for large-scale pre-training, with orthogonalization via Newton-Schulz (NS) iterations as its core operation. Existi…

cs.CV2026

ClinCoT: Clinical-Aware Visual Chain-of-Thought for Medical Vision Language Models

Xiwei Liu, Yulong Li, Xinlin Zhuang +5

Medical Vision-Language Models have shown promising potential in clinical decision support, yet they remain prone to factual hallucinations due to insufficient grounding in localiz…

cs.AI2026

DoAtlas-1: A Causal Compilation Paradigm for Clinical AI

Yulong Li, Jianxu Chen, Xiwei Liu +9

Medical foundation models generate narrative explanations but cannot quantify intervention effects, detect evidence conflicts, or validate literature claims, limiting clinical audi…

cs.CV2026

APEX: Learning Adaptive Priorities for Multi-Objective Alignment in Vision-Language Generation

Dongliang Chen, Xinlin Zhuang, Junjie Xu +8

Multi-objective alignment for text-to-image generation is commonly implemented via static linear scalarization, but fixed weights often fail under heterogeneous rewards, leading to…

cs.LG2025

CHIPS: Efficient CLIP Adaptation via Curvature-aware Hybrid Influence-based Data Selection

Xinlin Zhuang, Yichen Li, Xiwei Liu +11

Adapting CLIP to vertical domains is typically approached by novel fine-tuning strategies or by continual pre-training (CPT) on large domain-specific datasets. Yet, data itself rem…