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Xuanming Cui

4 accepted papers

2026

Think Then Embed: Generative Context Improves Multimodal Embedding

ICLR 2026poster

There is a growing interest in Universal Multimodal Embeddings (UME), where models are required to generate task-specific representations. While recent studies show that Multimodal Large Language Models (MLLMs) perform well on such tasks, they treat MLLMs solely as encoders, overlooking their genera…

Cited by 0SourceScholar
2025

Improving Soft Unification with Knowledge Graph Embedding Methods

ICML 2025poster

Neural Theorem Provers (NTPs) present a promising framework for neuro-symbolic reasoning, combining end-to-end differentiability with the interpretability of symbolic logic programming. However, optimizing NTPs remains a significant challenge due to their complex objective landscape and gradient spa…

Cited by 0SourcePDFScholar
2024

On the Robustness of Large Multimodal Models Against Image Adversarial Attacks

CVPR 2024poster

Recent advances in instruction tuning have led to the development of State-of-the-Art Large Multimodal Models (LMMs). Given the novelty of these models the impact of visual adversarial attacks on LMMs has not been thoroughly examined. We conduct a comprehensive study of the robustness of various LMM…

Cited by 39SourcePDFScholar