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Dual-grained Internal Refusal Estimation (DIRE), a training-free detection framework that jointly probes resilient Attention routing and FFN semantic memory within effective semantic layers to detect multimodal jailbreaks in a training-free manner, is introduced.
This work proposes a lightweight dual-domain attention aggregation network (LDANet), aiming to achieve image super-resolution with both high efficiency and high quality, and proposes the pixel-embedding channel attention module, which achieves cross-channel global context awareness by jointly modeling pixel-level spati...
SpectraMancer, which learns kernels directly in the Fourier spectral domain induced by multilevel circulant matrices, thereby enabling generalizable kernel learning for complex data and improves spectrum-aware kernel selection and predictive performance across diverse benchmarks.
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