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pro vyhledávání: '"Ajwani, Rohan"'
Large Language Models (LLMs) are becoming vital tools that help us solve and understand complex problems by acting as digital assistants. LLMs can generate convincing explanations, even when only given the inputs and outputs of these problems, i.e.,
Externí odkaz:
http://arxiv.org/abs/2405.06800
Publikováno v:
Presented at Deployable AI Workshop at AAAI-2024
Transformer-based Large Language Models (LLMs) have shown exceptional language generation capabilities in response to text-based prompts. However, controlling the direction of generation via textual prompts has been challenging, especially with small
Externí odkaz:
http://arxiv.org/abs/2404.05143
We present a Spiking Neural Network (SNN) based Sparse Distributed Memory (SDM) implemented on the Nengo framework. We have based our work on previous work by Furber et al, 2004, implementing SDM using N-of-M codes. As an integral part of the SDM des
Externí odkaz:
http://arxiv.org/abs/2109.03111
We present a Spiking Neural Network (SNN) based Sparse Distributed Memory (SDM) implemented on the Nengo framework. We have based our work on previous work by Furber et al, 2004, implementing SDM using N-of-M codes. As an integral part of the SDM des
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::29cbd0e4b0c04e20a42eefd80dea912c
http://arxiv.org/abs/2109.03111
http://arxiv.org/abs/2109.03111