1 citations · 1 across the 10 of their papers we have counts for
13 papers
Parse Before You Execute: Efficient Spatial Reasoning with Executable Primitives
Xiwei Liu, Yulong Li, Xinling Zhuang +5
Spatial reasoning in Vision-Language Models (VLMs) has increasingly benefited from tool-integrated pipelines that ground computation in explicit geometry. However, existing systems…
What Makes Recurrence Effective in Looped Language Models?
Xinlin Zhuang, Siyuan Wang, Imran Razzak +1
Looped language models (LoopLMs) increase computational depth through parameter sharing, offering a path to scale inference computation without adding parameters. However, it remai…
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…
AMO: Operator-level 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) iteration as its core operation. Standar…
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…
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…
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…
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…
Phenome-Wide Multi-Omics Integration Uncovers Distinct Archetypes of Human Aging
Huifa Li, Feilong Tang, Haochen Xue +5
Aging is a highly complex and heterogeneous process that progresses at different rates across individuals, making biological age (BA) a more accurate indicator of physiological dec…
Towards Robust Visual Continual Learning with Multi-Prototype Supervision
Xiwei Liu, Yulong Li, Yichen Li +4
Language-guided supervision, which utilizes a frozen semantic target from a Pretrained Language Model (PLM), has emerged as a promising paradigm for visual Continual Learning (CL).…
scAGC: Learning Adaptive Cell Graphs with Contrastive Guidance for Single-Cell Clustering
Huifa Li, Jie Fu, Xinlin Zhuang +6
Accurate cell type annotation is a crucial step in analyzing single-cell RNA sequencing (scRNA-seq) data, which provides valuable insights into cellular heterogeneity. However, due…
StreamAgent: Towards Anticipatory Agents for Streaming Video Understanding
Haolin Yang, Feilong Tang, Lingxiao Zhao +10
Real-time streaming video understanding in domains such as autonomous driving and intelligent surveillance poses challenges beyond conventional offline video processing, requiring…
Towards Efficient Medical Reasoning with Minimal Fine-Tuning Data
Xinlin Zhuang, Feilong Tang, Haolin Yang +9
Supervised Fine-Tuning (SFT) of the language backbone plays a pivotal role in adapting Vision-Language Models (VLMs) to specialized domains such as medical reasoning. However, exis…