10 accepted papers
Vision-Language Models (VLMs) have advanced multimodal understanding, yet they remain susceptible to adversarial attacks. Among various strategies, transfer-based attacks are notably effective, especially in black-box scenarios. The dominant approach within this paradigm leverages generative models
Existing video frame interpolation (VFI) methods often adopt a frame-centric approach, processing videos as independent short segments (e.g., triplets), which leads to temporal inconsistencies and motion artifacts. To overcome this, we propose a holistic, video-centric paradigm named Local Diffusion
Source-free domain adaptation (SFDA) is a challenging task that tackles domain shifts using only a pre-trained source model and unlabeled target data. Existing SFDA methods are restricted by the fundamental limitation of source-target domain discrepancy. Non-generation SFDA methods suffer from unrel…
Controllability of video generation has been recently concerned in addition to the quality of generated videos. The main challenge to controllable video generation is to synthesize videos based on user-specified instance spatial locations and movement trajectories. However, existing methods suffer f…
Low-bit integer training emerges as a promising approach to mitigate the heavy burden during network training by quantizing the weights, activations, and gradients. However, existing methods cannot well achieve mixed-precision quantization for low-bit training and are commonly limited to INT8 precis…
Topology augmentation is a popular strategy to address the issue of over-smoothing in graph neural networks (GNNs). To prevent potential distortion of node representations, an essential principle is to enhance the separability between embeddings of nodes from different classes while preserving smoot…
Following the rapid progress in natural language processing (NLP) models, language models are applied to increasingly more complex interactive tasks such as negotiations and conversation moderations. Having human evaluators directly interact with these NLP models is essential for adequately evaluati…
Conversational moderation of online communities is crucial to maintaining civility for a constructive environment, but it is challenging to scale and harmful to moderators. The inclusion of sophisticated natural language generation modules as a force multiplier to aid human moderators is a tantalizi…
"Synthesizing multi-view 3D from one single image is a significant but challenging task. Zero-1-to-3 methods have achieved great success by lifting a 2D latent diffusion model to the 3D scope. The target-view image is generated with a single-view source image and the camera pose as condition informa…
"Latent Diffusion Models (LDMs) are powerful and potential tools for facilitating generation-based methods for domain generalization. However, existing diffusion-based DG methods are restricted to offline augmentation using LDM and suffer from degraded performance and prohibitive computational costs…