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pro vyhledávání: '"Ramchandran P"'
With hundreds of thousands of language models available on Huggingface today, efficiently evaluating and utilizing these models across various downstream, tasks has become increasingly critical. Many existing methods repeatedly learn task-specific re
Externí odkaz:
http://arxiv.org/abs/2410.02223
Recent work has shown that Transformers trained from scratch can successfully solve various arithmetic and algorithmic tasks, such as adding numbers and computing parity. While these Transformers generalize well on unseen inputs of the same length, t
Externí odkaz:
http://arxiv.org/abs/2409.15647
Autor:
Rajaraman, Nived, Bondaschi, Marco, Ramchandran, Kannan, Gastpar, Michael, Makkuva, Ashok Vardhan
Attention-based transformers have been remarkably successful at modeling generative processes across various domains and modalities. In this paper, we study the behavior of transformers on data drawn from \kth Markov processes, where the conditional
Externí odkaz:
http://arxiv.org/abs/2407.17686
While there has been a large body of research attempting to circumvent tokenization for language modeling (Clark et al., 2022; Xue et al., 2022), the current consensus is that it is a necessary initial step for designing state-of-the-art performant l
Externí odkaz:
http://arxiv.org/abs/2404.08335
One of the key challenges in machine learning is to find interpretable representations of learned functions. The M\"obius transform is essential for this purpose, as its coefficients correspond to unique importance scores for sets of input variables.
Externí odkaz:
http://arxiv.org/abs/2402.02631
Publikováno v:
Journal of Community Hospital Internal Medicine Perspectives, Vol 9, Iss 1, Pp 33-35 (2019)
Statins are commonly used lipid lowering agents which play a pivotal role in reducing cardiovascular morbidity and mortality. Often well tolerated, these HMG-CoA reductase (HMGCR) inhibitors can sometimes cause severe muscle weakness and elevated cre
Externí odkaz:
https://doaj.org/article/54e062de2f4645cc82f4059c7b2494f5
Autor:
Huang, Baihe, Zhu, Hanlin, Zhu, Banghua, Ramchandran, Kannan, Jordan, Michael I., Lee, Jason D., Jiao, Jiantao
We study statistical watermarking by formulating it as a hypothesis testing problem, a general framework which subsumes all previous statistical watermarking methods. Key to our formulation is a coupling of the output tokens and the rejection region,
Externí odkaz:
http://arxiv.org/abs/2312.07930
Large Language Models (LLMs) can acquire extensive world knowledge through pre-training on large corpora. However, due to exposure to low-quality data, LLMs may exhibit harmful behavior without aligning with human values. The dominant approach for st
Externí odkaz:
http://arxiv.org/abs/2310.00212
Autor:
Swethal Ramchandran
Publikováno v:
IAFOR Journal of Arts & Humanities, Vol 11, Iss 1, Pp 115-125 (2024)
In literature, saga narratives stand out as a genre that closely follows the trajectories of various characters and families, navigating through stories that span ages, generations, and diverse regions. By centering on female protagonists, this genre
Externí odkaz:
https://doaj.org/article/fcba47189d53474db7f8aa1a4c7b9de9
Deep artificial neural networks achieve surprising generalization abilities that remain poorly understood. In this paper, we present a new approach to analyzing generalization for deep feed-forward ReLU networks that takes advantage of the degree of
Externí odkaz:
http://arxiv.org/abs/2307.00426