Zobrazeno 1 - 10
of 148
pro vyhledávání: '"Guha, Arjun"'
Autor:
Fiotto-Kaufman, Jaden, Loftus, Alexander R, Todd, Eric, Brinkmann, Jannik, Juang, Caden, Pal, Koyena, Rager, Can, Mueller, Aaron, Marks, Samuel, Sharma, Arnab Sen, Lucchetti, Francesca, Ripa, Michael, Belfki, Adam, Prakash, Nikhil, Multani, Sumeet, Brodley, Carla, Guha, Arjun, Bell, Jonathan, Wallace, Byron, Bau, David
The enormous scale of state-of-the-art foundation models has limited their accessibility to scientists, because customized experiments at large model sizes require costly hardware and complex engineering that is impractical for most researchers. To a
Externí odkaz:
http://arxiv.org/abs/2407.14561
Open-weight LLMs are particularly appealing choices to generate training data for fine-tuning Code LLMs on domain-specific service robot applications because they are cost-effective, customizable, and offer better privacy protection. However, unlike
Externí odkaz:
http://arxiv.org/abs/2405.20179
Autor:
Lucchetti, Francesca, Guha, Arjun
CodeLLMs are transforming software development as we know it. This is especially true for tasks where rule-based approaches fall short, like type prediction. The type prediction task consists in adding a new type annotation to a partially typed progr
Externí odkaz:
http://arxiv.org/abs/2404.01903
Autor:
Lozhkov, Anton, Li, Raymond, Allal, Loubna Ben, Cassano, Federico, Lamy-Poirier, Joel, Tazi, Nouamane, Tang, Ao, Pykhtar, Dmytro, Liu, Jiawei, Wei, Yuxiang, Liu, Tianyang, Tian, Max, Kocetkov, Denis, Zucker, Arthur, Belkada, Younes, Wang, Zijian, Liu, Qian, Abulkhanov, Dmitry, Paul, Indraneil, Li, Zhuang, Li, Wen-Ding, Risdal, Megan, Li, Jia, Zhu, Jian, Zhuo, Terry Yue, Zheltonozhskii, Evgenii, Dade, Nii Osae Osae, Yu, Wenhao, Krauß, Lucas, Jain, Naman, Su, Yixuan, He, Xuanli, Dey, Manan, Abati, Edoardo, Chai, Yekun, Muennighoff, Niklas, Tang, Xiangru, Oblokulov, Muhtasham, Akiki, Christopher, Marone, Marc, Mou, Chenghao, Mishra, Mayank, Gu, Alex, Hui, Binyuan, Dao, Tri, Zebaze, Armel, Dehaene, Olivier, Patry, Nicolas, Xu, Canwen, McAuley, Julian, Hu, Han, Scholak, Torsten, Paquet, Sebastien, Robinson, Jennifer, Anderson, Carolyn Jane, Chapados, Nicolas, Patwary, Mostofa, Tajbakhsh, Nima, Jernite, Yacine, Ferrandis, Carlos Muñoz, Zhang, Lingming, Hughes, Sean, Wolf, Thomas, Guha, Arjun, von Werra, Leandro, de Vries, Harm
The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership with Software Heritage (SWH), we build The Stack v2 on top of the digita
Externí odkaz:
http://arxiv.org/abs/2402.19173
Autor:
Nguyen, Sydney, Babe, Hannah McLean, Zi, Yangtian, Guha, Arjun, Anderson, Carolyn Jane, Feldman, Molly Q
Generative AI models, specifically large language models (LLMs), have made strides towards the long-standing goal of text-to-code generation. This progress has invited numerous studies of user interaction. However, less is known about the struggles a
Externí odkaz:
http://arxiv.org/abs/2401.15232
Autor:
Cassano, Federico, Li, Luisa, Sethi, Akul, Shinn, Noah, Brennan-Jones, Abby, Ginesin, Jacob, Berman, Edward, Chakhnashvili, George, Lozhkov, Anton, Anderson, Carolyn Jane, Guha, Arjun
A significant amount of research is focused on developing and evaluating large language models for a variety of code synthesis tasks. These include synthesizing code from natural language, synthesizing tests from code, and synthesizing explanations o
Externí odkaz:
http://arxiv.org/abs/2312.12450
Autor:
Hu, Zichao, Lucchetti, Francesca, Schlesinger, Claire, Saxena, Yash, Freeman, Anders, Modak, Sadanand, Guha, Arjun, Biswas, Joydeep
Publikováno v:
IEEE Robotics and Automation Letters, vol. 9, no. 3, pp. 2853-2860, March 2024
Recent advancements in large language models (LLMs) have spurred interest in using them for generating robot programs from natural language, with promising initial results. We investigate the use of LLMs to generate programs for service mobile robots
Externí odkaz:
http://arxiv.org/abs/2311.11183
Software developers typically rely upon a large network of dependencies to build their applications. For instance, the NPM package repository contains over 3 million packages and serves tens of billions of downloads weekly. Understanding the structur
Externí odkaz:
http://arxiv.org/abs/2308.12545
Autor:
Cassano, Federico, Gouwar, John, Lucchetti, Francesca, Schlesinger, Claire, Freeman, Anders, Anderson, Carolyn Jane, Feldman, Molly Q, Greenberg, Michael, Jangda, Abhinav, Guha, Arjun
Over the past few years, Large Language Models of Code (Code LLMs) have started to have a significant impact on programming practice. Code LLMs are also emerging as building blocks for research in programming languages and software engineering. Howev
Externí odkaz:
http://arxiv.org/abs/2308.09895
Autor:
Phipps-Costin, Luna, Rossberg, Andreas, Guha, Arjun, Leijen, Daan, Hillerström, Daniel, Sivaramakrishnan, KC, Pretnar, Matija, Lindley, Sam
WebAssembly (Wasm) is a low-level portable code format offering near native performance. It is intended as a compilation target for a wide variety of source languages. However, Wasm provides no direct support for non-local control flow features such
Externí odkaz:
http://arxiv.org/abs/2308.08347