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Token Pruning for Caching Better: 9 Times Acceleration on Stable Diffusion for Free
Evelyn Zhang, Bang Xiao, Jiayi Tang +5
Stable Diffusion has achieved remarkable success in the field of text-to-image generation, with its powerful generative capabilities and diverse generation results making a lasting…
MAGIC++: Efficient and Resilient Modality-Agnostic Semantic Segmentation via Hierarchical Modality Selection
Xu Zheng, Yuanhuiyi Lyu, Lutao Jiang +3
In this paper, we address the challenging modality-agnostic semantic segmentation (MaSS), aiming at centering the value of every modality at every feature granularity. Training wit…
SAVEn-Vid: Synergistic Audio-Visual Integration for Enhanced Understanding in Long Video Context
Jungang Li, Sicheng Tao, Yibo Yan +6
Endeavors have been made to explore Large Language Models for video analysis (Video-LLMs), particularly in understanding and interpreting long videos. However, existing Video-LLMs…
Rethinking Token-wise Feature Caching: Accelerating Diffusion Transformers with Dual Feature Caching
Chang Zou, Shikang Zheng, Evelyn Zhang +6
Diffusion Transformers (DiT) have become the dominant methods in image and video generation yet still suffer substantial computational costs. As an effective approach for DiT accel…
ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models
Junzhe Chen, Tianshu Zhang, Shiyu Huang +4
Despite the recent breakthroughs achieved by Large Vision Language Models (LVLMs) in understanding and responding to complex visual-textual contexts, their inherent hallucination t…
Learning Robust Anymodal Segmentor with Unimodal and Cross-modal Distillation
Xu Zheng, Haiwei Xue, Jialei Chen +6
Simultaneously using multimodal inputs from multiple sensors to train segmentors is intuitively advantageous but practically challenging. A key challenge is unimodal bias, where mu…
Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Transformers
Shaobo Wang, Hongxuan Tang, Mingyang Wang +5
The debate between self-interpretable models and post-hoc explanations for black-box models is central to Explainable AI (XAI). Self-interpretable models, such as concept-based net…
DRUPI: Dataset Reduction Using Privileged Information
Shaobo Wang, Youxin Jiang, Tianle Niu +9
Dataset Condensation (DC) seeks to select or distill samples from large datasets into smaller subsets while preserving performance on target tasks. Existing methods primarily focus…