most citedMetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Learning to Reason by Analogy via Retrieval-Augmented Reinforcement Fine-Tuning

Zilin Xiao, Qi Ma, Chun-cheng Jason Chen +4

Retrieval-augmented generation (RAG) has become a standard mechanism for grounding language models in external knowledge, yet conventional retrieval based on lexical or semantic si…

cs.CV2025

Unsupervised Multi-View Visual Anomaly Detection via Progressive Homography-Guided Alignment

Xintao Chen, Xiaohao Xu, Bozhong Zheng +2

Unsupervised visual anomaly detection from multi-view images presents a significant challenge: distinguishing genuine defects from benign appearance variations caused by viewpoint…

cs.IR2025★ 1 cited

MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction

Zilin Xiao, Qi Ma, Mengting Gu +4

Universal multimodal embedding models have achieved great success in capturing semantic relevance between queries and candidates. However, current methods either condense queries a…

cs.CV2025

Bridging 3D Anomaly Localization and Repair via High-Quality Continuous Geometric Representation

Bozhong Zheng, Jinye Gan, Xiaohao Xu +5

3D point cloud anomaly detection is essential for robust vision systems but is challenged by pose variations and complex geometric anomalies. Existing patch-based methods often suf…

cs.CV2025

Towards Visual Discrimination and Reasoning of Real-World Physical Dynamics: Physics-Grounded Anomaly Detection

Wenqiao Li, Yao Gu, Xintao Chen +4

Humans detect real-world object anomalies by perceiving, interacting, and reasoning based on object-conditioned physical knowledge. The long-term goal of Industrial Anomaly Detecti…