Zobrazeno 1 - 10
of 18 090
pro vyhledávání: '"A. Aishwarya"'
Autor:
Aishwarya, Gautam, Li, Dongbin
The Kneser--Poulsen conjecture asserts that the volume of a union of balls in Euclidean space cannot be increased by bringing their centres pairwise closer. We prove that its natural information-theoretic counterpart is true. This follows from a comp
Externí odkaz:
http://arxiv.org/abs/2409.03664
We consider the problem of independently, in a disentangled fashion, controlling the outputs of text-to-image diffusion models with color and style attributes of a user-supplied reference image. We present the first training-free, test-time-only meth
Externí odkaz:
http://arxiv.org/abs/2409.02429
Current quantum generative adversarial networks (QGANs) still struggle with practical-sized data. First, many QGANs use principal component analysis (PCA) for dimension reduction, which, as our studies reveal, can diminish the QGAN's effectiveness. S
Externí odkaz:
http://arxiv.org/abs/2409.02212
Antarctic ice shelves play a vital role in preserving the physical conditions of the Antarctic cryosphere and the Southern Ocean, and beyond. By serving as a buttressing force, ice shelves prevent sea-level rise by restraining the flow of continental
Externí odkaz:
http://arxiv.org/abs/2408.12106
Rigorous testing of machine learning models is necessary for trustworthy deployments. We present a novel black-box approach for generating test-suites for robust testing of deep neural networks (DNNs). Most existing methods create test inputs based o
Externí odkaz:
http://arxiv.org/abs/2408.06766
Fine-grained understanding of objects, attributes, and relationships between objects is crucial for visual-language models (VLMs). Existing benchmarks primarily focus on evaluating VLMs' capability to distinguish between two very similar \textit{capt
Externí odkaz:
http://arxiv.org/abs/2407.16772
Autor:
Jadhav, Aishwarya, Dutt, Ritam
The task of searching through patent documents is crucial for chemical patent recommendation and retrieval. This can be enhanced by creating a patent knowledge base (ChemPatKB) to aid in prior art searches and to provide a platform for domain experts
Externí odkaz:
http://arxiv.org/abs/2407.15124
Autor:
Nayak, Shravan, Jain, Kanishk, Awal, Rabiul, Reddy, Siva, van Steenkiste, Sjoerd, Hendricks, Lisa Anne, Stańczak, Karolina, Agrawal, Aishwarya
Foundation models and vision-language pre-training have notably advanced Vision Language Models (VLMs), enabling multimodal processing of visual and linguistic data. However, their performance has been typically assessed on general scene understandin
Externí odkaz:
http://arxiv.org/abs/2407.10920
Despite tremendous advancements, current state-of-the-art Vision-Language Models (VLMs) are still far from perfect. They tend to hallucinate and may generate biased responses. In such circumstances, having a way to assess the reliability of a given r
Externí odkaz:
http://arxiv.org/abs/2407.07840
In recent years, Natural Language Processing (NLP) has played a significant role in various Artificial Intelligence (AI) applications such as chatbots, text generation, and language translation. The emergence of large language models (LLMs) has great
Externí odkaz:
http://arxiv.org/abs/2407.06564