2 citations · 2 across the 15 of their papers we have counts for
6 papers · 1 filter
A Model-Internal Protocol for Assessing Multimodal Models as Integrated Systems
Hao Zhang, Jiaxin Qi, Zhijiang Tang +1
As Large Vision-Language Models increasingly aim to integrate visual generation and understanding within a single parameter space, evaluating such structural unification in a cohes…
A Reconstruction-Based Framework for Caption Evaluation Beyond Reference Captions
Zhijiang Tang, Jiaxin Qi, Kaihua Tang +2
Image captioning is a primary task in vision--language research, yet assessing how faithfully a caption preserves image semantics without relying on reference captions remains unse…
Intrinsic Gradient Suppression for Label-Noise Prompt Tuning in Vision-Language Models
Jiayu Li, Jiaxin Qi, Sheng Zhou +2
Contrastive vision-language models like CLIP exhibit remarkable zero-shot generalization. However, prompt tuning remains highly sensitive to label noise, as mislabeled samples gene…
Long-CODE: Isolating Pure Long-Context as an Orthogonal Dimension in Video Evaluation
Zhijiang Tang, Jiaxin Qi, Bing Zhao +1
As video generation models achieve unprecedented capabilities, the demand for robust video evaluation metrics becomes increasingly critical. Traditional metrics are intrinsically t…
Scaling Test-Time Robustness of Vision-Language Models via Self-Critical Inference Framework
Kaihua Tang, Jiaxin Qi, Jinli Ou +2
The emergence of Large Language Models (LLMs) has driven rapid progress in multi-modal learning, particularly in the development of Large Vision-Language Models (LVLMs). However, e…
Spatial Transcriptomics as Images for Large-Scale Pretraining
Yishun Zhu, Jiaxin Qi, Jian Wang +2
Spatial Transcriptomics (ST) profiles thousands of gene expression values at discrete spots with precise coordinates on tissue sections, preserving spatial context essential for cl…