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pro vyhledávání: '"Choo, A"'
Autor:
Ding, Mucong, Deng, Chenghao, Choo, Jocelyn, Wu, Zichu, Agrawal, Aakriti, Schwarzschild, Avi, Zhou, Tianyi, Goldstein, Tom, Langford, John, Anandkumar, Anima, Huang, Furong
While generalization over tasks from easy to hard is crucial to profile language models (LLMs), the datasets with fine-grained difficulty annotations for each problem across a broad range of complexity are still blank. Aiming to address this limitati
Externí odkaz:
http://arxiv.org/abs/2409.18433
A growing research explores the usage of AI explanations on user's decision phases for human-AI collaborative decision-making. However, previous studies found the issues of overreliance on `wrong' AI outputs. In this paper, we propose interactive exa
Externí odkaz:
http://arxiv.org/abs/2409.15814
Recently, 3D Gaussian splatting has been getting a lot of attention as an innovative method for representing 3D space due to rapid rendering and image quality. However, copyright protection for the 3D Gaussian splatting has not yet been introduced. I
Externí odkaz:
http://arxiv.org/abs/2409.13222
Recommender systems are essential for personalizing digital experiences on e-commerce sites, streaming services, and social media platforms. While these systems are necessary for modern digital interactions, they face fairness, bias, threats, and pri
Externí odkaz:
http://arxiv.org/abs/2409.12651
Autism Spectrum Disorder (ASD) significantly affects the social and communication abilities of children, and eye-tracking is commonly used as a diagnostic tool by identifying associated atypical gaze patterns. Traditional methods demand manual identi
Externí odkaz:
http://arxiv.org/abs/2409.11744
Recent advances in interactive keypoint estimation methods have enhanced accuracy while minimizing user intervention. However, these methods require user input for error correction, which can be costly in vertebrae keypoint estimation where inaccurat
Externí odkaz:
http://arxiv.org/abs/2409.03261
Autor:
Jo, Kyungmin, Choo, Jaegul
The emergence of diffusion models has enabled the generation of diverse high-quality images solely from text, prompting subsequent efforts to enhance the controllability of these models. Despite the improvement in controllability, pose control remain
Externí odkaz:
http://arxiv.org/abs/2409.02653
Hairstyle transfer is a challenging task in the image editing field that modifies the hairstyle of a given face image while preserving its other appearance and background features. The existing hairstyle transfer approaches heavily rely on StyleGAN,
Externí odkaz:
http://arxiv.org/abs/2408.16450
We propose a unified framework for robustly and adaptively stabilizing large-scale networked uncertain Markovian jump linear systems (MJLS) under external disturbances and mode switches that can change the network's topology. Adaptation is achieved b
Externí odkaz:
http://arxiv.org/abs/2408.15789
Despite the growing prevalence of black-box pre-trained models (PTMs) such as prediction API services, there remains a significant challenge in directly applying general models to real-world scenarios due to the data distribution gap. Considering a d
Externí odkaz:
http://arxiv.org/abs/2408.07944