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pro vyhledávání: '"Pan,Rui"'
Instruction tuning has achieved unprecedented success in NLP, turning large language models into versatile chatbots. However, the increasing variety and volume of instruction datasets demand significant computational resources. To address this, it is
Externí odkaz:
http://arxiv.org/abs/2407.15235
Interoperability is a significant challenge in blockchain technology, hindering seamless data and service sharing across diverse blockchain networks. This study introduces Automated Gateways as a novel framework leveraging smart contracts to facilita
Externí odkaz:
http://arxiv.org/abs/2407.13001
Autor:
Ting, Yuan-Sen, Nguyen, Tuan Dung, Ghosal, Tirthankar, Pan, Rui, Arora, Hardik, Sun, Zechang, de Haan, Tijmen, Ramachandra, Nesar, Wells, Azton, Madireddy, Sandeep, Accomazzi, Alberto
We present a comprehensive evaluation of proprietary and open-weights large language models using the first astronomy-specific benchmarking dataset. This dataset comprises 4,425 multiple-choice questions curated from the Annual Review of Astronomy an
Externí odkaz:
http://arxiv.org/abs/2407.11194
Proving mathematical theorems using computer-verifiable formal languages like Lean significantly impacts mathematical reasoning. One approach to formal theorem proving involves generating complete proofs using Large Language Models (LLMs) based on Na
Externí odkaz:
http://arxiv.org/abs/2407.03203
Bilevel optimization has shown its utility across various machine learning settings, yet most algorithms in practice require second-order information, making it challenging to scale them up. Only recently, a paradigm of first-order algorithms emerged
Externí odkaz:
http://arxiv.org/abs/2406.19976
Adaptive gradient algorithms have been widely adopted in training large-scale deep neural networks, especially large foundation models. Despite their huge success in practice, their theoretical advantages over stochastic gradient descent (SGD) have n
Externí odkaz:
http://arxiv.org/abs/2406.15244
Image description datasets play a crucial role in the advancement of various applications such as image understanding, text-to-image generation, and text-image retrieval. Currently, image description datasets primarily originate from two sources. One
Externí odkaz:
http://arxiv.org/abs/2406.07502
In this paper, we systematically study the evolution of the Universe in the framework of a modified loop quantum cosmological model (mLQC-I) with various inflationary potentials, including chaotic, Starobinsky, generalized Starobinsky, polynomials of
Externí odkaz:
http://arxiv.org/abs/2406.06745
In this study, we develop a latent factor model for analysing high-dimensional binary data. Specifically, a standard probit model is used to describe the regression relationship between the observed binary data and the continuous latent variables. Ou
Externí odkaz:
http://arxiv.org/abs/2404.08457
The machine learning community has witnessed impressive advancements since large language models (LLMs) first appeared. Yet, their massive memory consumption has become a significant roadblock to large-scale training. For instance, a 7B model typical
Externí odkaz:
http://arxiv.org/abs/2403.17919