Zobrazeno 1 - 10
of 32 200
pro vyhledávání: '"Leonid, P."'
Deep neural networks (DNNs) offer significant promise for improving breast cancer diagnosis in medical imaging. However, these models are highly susceptible to adversarial attacks--small, imperceptible changes that can mislead classifiers--raising cr
Externí odkaz:
http://arxiv.org/abs/2412.09910
Vision-Language Models (VLMs) achieved strong performance on a variety of tasks (e.g., image-text retrieval, visual question answering). However, most VLMs rely on coarse-grained image-caption pairs for alignment, relying on data volume to resolve am
Externí odkaz:
http://arxiv.org/abs/2412.08110
Autor:
Antsfeld, Leonid, Chidlovskii, Boris
We address the problem of 3D inconsistency of image inpainting based on diffusion models. We propose a generative model using image pairs that belong to the same scene. To achieve the 3D-consistent and semantically coherent inpainting, we modify the
Externí odkaz:
http://arxiv.org/abs/2412.05881
The commonsense reasoning capabilities of vision-language models (VLMs), especially in abductive reasoning and defeasible reasoning, remain poorly understood. Most benchmarks focus on typical visual scenarios, making it difficult to discern whether m
Externí odkaz:
http://arxiv.org/abs/2412.05725
Autor:
Bunimovich, Leonid A., Su, Yaofeng
The paper addresses some basic questions in the theory of finite time dynamics and finite time predictions for non-uniformly hyperbolic dynamical systems. We are concerned with transport in phase spaces of such systems, and analyze which subsets and
Externí odkaz:
http://arxiv.org/abs/2412.04615
Latent variable generative models have emerged as powerful tools for generative tasks including image and video synthesis. These models are enabled by pretrained autoencoders that map high resolution data into a compressed lower dimensional latent sp
Externí odkaz:
http://arxiv.org/abs/2412.04452
Autor:
Yasunaga, Michihiro, Shamis, Leonid, Zhou, Chunting, Cohen, Andrew, Weston, Jason, Zettlemoyer, Luke, Ghazvininejad, Marjan
Recent approaches to large language model (LLM) alignment typically require millions of human annotations or rely on external aligned models for synthetic data generation. This paper introduces ALMA: Alignment with Minimal Annotation, demonstrating t
Externí odkaz:
http://arxiv.org/abs/2412.04305
Although open-vocabulary classification models like Contrastive Language Image Pretraining (CLIP) have demonstrated strong zero-shot learning capabilities, their robustness to common image corruptions remains poorly understood. Through extensive expe
Externí odkaz:
http://arxiv.org/abs/2412.02837
Autor:
Kotyuzanskiy, Leonid, Klimov, Artem
The transformer architecture has become an integral part of the field of modern neural networks, playing a crucial role in a variety of tasks, such as text generation, machine translation, image and audio processing, among others. There is also an al
Externí odkaz:
http://arxiv.org/abs/2412.00503
The issue of inheriting periodicity of an exact solution of a dynamic system by a difference scheme is considered. It is shown that some difference schemes (midpoint scheme, Kahan scheme) in some special cases provide approximate solutions of differe
Externí odkaz:
http://arxiv.org/abs/2412.00388