activity
20242026
collaborators

8 papers

cs.CV2026

FBCIR: Balancing Cross-Modal Focuses in Composed Image Retrieval

Chenchen Zhao, Jianhuan Zhuo, Muxi Chen +6

Composed image retrieval (CIR) requires multi-modal models to jointly reason over visual content and semantic modifications presented in text-image input pairs. While current CIR m…

cs.CV2026

\textit{FocaLogic}: Logic-Based Interpretation of Visual Model Decisions

Chenchen Zhao, Muxi Chen, Qiang Xu

Interpretability of modern visual models is crucial, particularly in high-stakes applications. However, existing interpretability methods typically suffer from either reliance on w…

cs.CL2025

Activations as Features: Probing LLMs for Generalizable Essay Scoring Representations

Jinwei Chi, Ke Wang, Yu Chen +2

Automated essay scoring (AES) is a challenging task in cross-prompt settings due to the diversity of scoring criteria. While previous studies have focused on the output of large la…

cs.CV2025

FailureAtlas:Mapping the Failure Landscape of T2I Models via Active Exploration

Muxi Chen, Zhaohua Zhang, Chenchen Zhao +8

Static benchmarks have provided a valuable foundation for comparing Text-to-Image (T2I) models. However, their passive design offers limited diagnostic power, struggling to uncover…

cs.LG2025

Concept-SAE: A Controllable and Invertible Concept Interface for Sparse Autoencoders

Jianrong Ding, Muxi Chen, Chenchen Zhao +1

Standard Sparse Autoencoders (SAEs) excel at discovering a dictionary of a model's learned features, providing a powerful lens for passive feature discovery. However, this passive…

cs.CV2025

MPCAR: Multi-Perspective Contextual Augmentation for Enhanced Visual Reasoning in Large Vision-Language Models

Amirul Rahman, Qiang Xu, Xueying Huang

Despite significant advancements, Large Vision-Language Models (LVLMs) continue to face challenges in complex visual reasoning tasks that demand deep contextual understanding, mult…

cs.CV2025

HiBug2: Efficient and Interpretable Error Slice Discovery for Comprehensive Model Debugging

Muxi Chen, Chenchen Zhao, Qiang Xu

Despite the significant success of deep learning models in computer vision, they often exhibit systematic failures on specific data subsets, known as error slices. Identifying and…

cs.HC2024

From Graphs to Words: A Computer-Assisted Framework for the Production of Accessible Text Descriptions

Qiang Xu, Thomas Hurtut

In the digital landscape, the ubiquity of data visualizations in media underscores the necessity for accessibility to ensure inclusivity for all users, including those with visual…