Author

Qi Chu

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#artificial intelligence Open access Sep 2026

SPIDER: Multi-Layer Semantic Token Pruning and Adaptive Sub-Layer Skipping in Multimodal Large Language Models.

It is proposed that intermediate layer tokens from vision encoders should be considered for effective visual token pruning, as semantic focus shifts across layers, with middle-layer tokens capturing more detailed object-centric information that deeper layers may abstract away.

Tian-Xiang Chen, Zhentao Tan, Zi Ye et al. · IEEE Transactions on Pattern... · 0 citations

#generative ai Preprint Sep 2026

EraseSAE: Surgical Concept Erasure in Text-to-Video Diffusion Models via Sparse Autoencoders

This work proposes EraseSAE, a novel framework that leverages sparse autoencoders to achieve surgical concept erasure in DiT-based T2V diffusion models via a principled decompose-attribute-erase pipeline, and introduces the Partitioned Convolutional Sparse Autoencoder.

Xing-Hao Wang, Dong Li, Wei Yu et al. · 0 citations

#artificial intelligence Preprint Sep 2026

TimeSteer: Inference-Time Speech Scheduling in Joint Audio-Visual Diffusion Models

A training-free framework that localizes each utterance's source span through Source Span Localization and transfers the associated audio-visual latent content from the source interval to the specified target interval through Region-Aware Latent Remapping is proposed.

Chao Zhou, Yilu Chen, Qi Chu et al. · 0 citations