Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Anderson, Carolyn Jane"'
Autor:
Yang, Funing, Anderson, Carolyn Jane
Several systems have been developed to extract information about characters to aid computational analysis of English literature. We propose character similarity grouping as a holistic evaluation task for these pipelines. We present AustenAlike, a ben
Externí odkaz:
http://arxiv.org/abs/2408.16131
Vision-Language Models (VLMs) building upon the foundation of powerful large language models have made rapid progress in reasoning across visual and textual data. While VLMs perform well on vision tasks that they are trained on, our results highlight
Externí odkaz:
http://arxiv.org/abs/2408.05894
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:
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:
Zhao, Jingmiao, Anderson, Carolyn Jane
We explore the ability of large language models to solve and generate puzzles from the NPR Sunday Puzzle game show using PUZZLEQA, a dataset comprising 15 years of on-air puzzles. We evaluate four large language models using PUZZLEQA, in both multipl
Externí odkaz:
http://arxiv.org/abs/2306.12255
Autor:
Babe, Hannah McLean, Nguyen, Sydney, Zi, Yangtian, Guha, Arjun, Feldman, Molly Q, Anderson, Carolyn Jane
Code LLMs are being rapidly deployed and there is evidence that they can make professional programmers more productive. Current benchmarks for code generation measure whether models generate correct programs given an expert prompt. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2306.04556
Autor:
Li, Raymond, Allal, Loubna Ben, Zi, Yangtian, Muennighoff, Niklas, Kocetkov, Denis, Mou, Chenghao, Marone, Marc, Akiki, Christopher, Li, Jia, Chim, Jenny, Liu, Qian, Zheltonozhskii, Evgenii, Zhuo, Terry Yue, Wang, Thomas, Dehaene, Olivier, Davaadorj, Mishig, Lamy-Poirier, Joel, Monteiro, João, Shliazhko, Oleh, Gontier, Nicolas, Meade, Nicholas, Zebaze, Armel, Yee, Ming-Ho, Umapathi, Logesh Kumar, Zhu, Jian, Lipkin, Benjamin, Oblokulov, Muhtasham, Wang, Zhiruo, Murthy, Rudra, Stillerman, Jason, Patel, Siva Sankalp, Abulkhanov, Dmitry, Zocca, Marco, Dey, Manan, Zhang, Zhihan, Fahmy, Nour, Bhattacharyya, Urvashi, Yu, Wenhao, Singh, Swayam, Luccioni, Sasha, Villegas, Paulo, Kunakov, Maxim, Zhdanov, Fedor, Romero, Manuel, Lee, Tony, Timor, Nadav, Ding, Jennifer, Schlesinger, Claire, Schoelkopf, Hailey, Ebert, Jan, Dao, Tri, Mishra, Mayank, Gu, Alex, Robinson, Jennifer, Anderson, Carolyn Jane, Dolan-Gavitt, Brendan, Contractor, Danish, Reddy, Siva, Fried, Daniel, Bahdanau, Dzmitry, Jernite, Yacine, Ferrandis, Carlos Muñoz, Hughes, Sean, Wolf, Thomas, Guha, Arjun, von Werra, Leandro, de Vries, Harm
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context length, infilling capabilitie
Externí odkaz:
http://arxiv.org/abs/2305.06161
Autor:
Allal, Loubna Ben, Li, Raymond, Kocetkov, Denis, Mou, Chenghao, Akiki, Christopher, Ferrandis, Carlos Munoz, Muennighoff, Niklas, Mishra, Mayank, Gu, Alex, Dey, Manan, Umapathi, Logesh Kumar, Anderson, Carolyn Jane, Zi, Yangtian, Poirier, Joel Lamy, Schoelkopf, Hailey, Troshin, Sergey, Abulkhanov, Dmitry, Romero, Manuel, Lappert, Michael, De Toni, Francesco, del Río, Bernardo García, Liu, Qian, Bose, Shamik, Bhattacharyya, Urvashi, Zhuo, Terry Yue, Yu, Ian, Villegas, Paulo, Zocca, Marco, Mangrulkar, Sourab, Lansky, David, Nguyen, Huu, Contractor, Danish, Villa, Luis, Li, Jia, Bahdanau, Dzmitry, Jernite, Yacine, Hughes, Sean, Fried, Daniel, Guha, Arjun, de Vries, Harm, von Werra, Leandro
The BigCode project is an open-scientific collaboration working on the responsible development of large language models for code. This tech report describes the progress of the collaboration until December 2022, outlining the current state of the Per
Externí odkaz:
http://arxiv.org/abs/2301.03988