This work identifies a vulnerability specific to diffusion generation: because the visual embedding conditions every reverse denoising step rather than acting as a one-time prefix, adversarial visual semantics are repeatedly propagated and amplified across the generation trajectory, a phenomenon the authors term cross-...
Guo-Rui Song, Run-Qing Tang, Jing-Ye Zhang et al.· 0 citations
This work proposes Retrv-MoE, a unified retrieval architecture built upon sparse Mixture-of-Experts (MoE), and theoretically and empirically demonstrates that this conditional computation mechanism provides a structural remedy to optimization interference by decoupling the learning trajectories of conflicting tasks and...
Tongxu Lin, Jiayin Xiao· Proceedings of the 32nd ACM...· 0 citations
Unified multimodal retrieval aims to build a single system capable of handling diverse modalities, tasks, and domains. While recent approaches leveraging multimodal large language models (MLLMs) have shown promise, they face a fundamental dilemma between capacity and interference: scaling dense models improves semantic...
Tongxu Lin, Jiayin Xiao· Proceedings of the 32nd ACM...· 0 citations
A novel inference-time intervention method that encodes truthful and untruthful content as an entailment hierarchy and performs representation editing in the hyperbolic space to activate the truthfulness of LLMs is proposed.
Tongxu Lin, Junping Du, Zhe Xue et al.· Proceedings of the 32nd ACM...· 0 citations
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