activity
20232026
most citedRevolutionizing Finance with LLMs: An Overview of Applications and Insights

43 citations · 161 across the 42 of their papers we have counts for

collaborators
Showing cs.CVShow all

11 papers · 1 filter

cs.CV2026

Who Speaks for the Pruned? Visual Token Pruning as Coverage Optimization

Qingchan Zhu, Weihang You, Hanqi Jiang +3

Visual token pruning reduces the inference cost of vision-language models (VLMs), but most methods only ask which tokens to keep. This retained-token view can keep redundant high-s…

cs.CV2026

MedVIGIL: Evaluating Trustworthy Medical VLMs Under Broken Visual Evidence

Hanqi Jiang, Junhao Chen, Mingyu Kang +12

Medical vision--language models (VLMs) are usually evaluated on intact image--question pairs, but trustworthy clinical use requires a stronger property: a model must recognise when…

cs.CV2026

Thinking with Gaze: Sequential Eye-Tracking as Visual Reasoning Supervision for Medical VLMs

Yiwei Li, Yifan Zhou, Huaqin Zhao +6

Vision--language models (VLMs) process images as visual tokens, yet their intermediate reasoning is often carried out in text, which can be suboptimal for visually grounded radiolo…

cs.CV2026

Neural Functional Alignment Space: Brain-Referenced Representation of Artificial Neural Networks

Ruiyu Yan, Hanqi Jiang, Yi Pan +4

We propose the Neural Functional Alignment Space (NFAS), a brain-referenced representational framework for characterizing artificial neural networks on equal functional grounds. NF…

cs.CV2026

ViThinker: Active Vision-Language Reasoning via Dynamic Perceptual Querying

Weihang You, Qingchan Zhu, David Liu +3

Chain-of-Thought (CoT) reasoning excels in language models but struggles in vision-language models due to premature visual-to-text conversion that discards continuous information s…

cs.CV2026

Achieving Fine-grained Cross-modal Understanding through Brain-inspired Hierarchical Representation Learning

Weihang You, Hanqi Jiang, Yi Pan +3

Understanding neural responses to visual stimuli remains challenging due to the inherent complexity of brain representations and the modality gap between neural data and visual inp…

cs.CV2025

AdCare-VLM: Towards a Unified and Pre-aligned Latent Representation for Healthcare Video Understanding

Md Asaduzzaman Jabin, Hanqi Jiang, Yiwei Li +4

Chronic diseases, including diabetes, hypertension, asthma, HIV-AIDS, epilepsy, and tuberculosis, necessitate rigorous adherence to medication to avert disease progression, manage…

cs.CV2024★ 2 cited

OracleSage: Towards Unified Visual-Linguistic Understanding of Oracle Bone Scripts through Cross-Modal Knowledge Fusion

Hanqi Jiang, Yi Pan, Junhao Chen +8

Oracle bone script (OBS), as China's earliest mature writing system, present significant challenges in automatic recognition due to their complex pictographic structures and diverg…

cs.CV2024

Advancing Medical Radiograph Representation Learning: A Hybrid Pre-training Paradigm with Multilevel Semantic Granularity

Hanqi Jiang, Xixuan Hao, Yuzhou Huang +4

This paper introduces an innovative approach to Medical Vision-Language Pre-training (Med-VLP) area in the specialized context of radiograph representation learning. While conventi…

cs.CV2024

Examining the Commitments and Difficulties Inherent in Multimodal Foundation Models for Street View Imagery

Zhenyuan Yang, Xuhui Lin, Qinyi He +10

The emergence of Large Language Models (LLMs) and multimodal foundation models (FMs) has generated heightened interest in their applications that integrate vision and language. Thi…

cs.CV2024★ 2 cited

Eye-gaze Guided Multi-modal Alignment for Medical Representation Learning

Chong Ma, Hanqi Jiang, Wenting Chen +10

In the medical multi-modal frameworks, the alignment of cross-modality features presents a significant challenge. However, existing works have learned features that are implicitly…