Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Fu, Quchen"'
This paper presents prompt design techniques for software engineering, in the form of patterns, to solve common problems when using large language models (LLMs), such as ChatGPT to automate common software engineering activities, such as ensuring cod
Externí odkaz:
http://arxiv.org/abs/2303.07839
Autor:
White, Jules, Fu, Quchen, Hays, Sam, Sandborn, Michael, Olea, Carlos, Gilbert, Henry, Elnashar, Ashraf, Spencer-Smith, Jesse, Schmidt, Douglas C.
Prompt engineering is an increasingly important skill set needed to converse effectively with large language models (LLMs), such as ChatGPT. Prompts are instructions given to an LLM to enforce rules, automate processes, and ensure specific qualities
Externí odkaz:
http://arxiv.org/abs/2302.11382
Publikováno v:
Journal of Machine Learning Theory, Applications and Practice 2023
Translating natural language into Bash Commands is an emerging research field that has gained attention in recent years. Most efforts have focused on producing more accurate translation models. To the best of our knowledge, only two datasets are avai
Externí odkaz:
http://arxiv.org/abs/2302.07845
Meetings are an essential form of communication for all types of organizations, and remote collaboration systems have been much more widely used since the COVID-19 pandemic. One major issue with remote meetings is that it is challenging for remote pa
Externí odkaz:
http://arxiv.org/abs/2210.13334
Autor:
Fu, Quchen, Chukka, Ramesh, Achorn, Keith, Atta-fosu, Thomas, Canchi, Deepak R., Teng, Zhongwei, White, Jules, Schmidt, Douglas C.
Publikováno v:
Journal of Machine Learning Theory, Applications and Practice (2023)
GPUs have been favored for training deep learning models due to their highly parallelized architecture. As a result, most studies on training optimization focus on GPUs. There is often a trade-off, however, between cost and efficiency when deciding o
Externí odkaz:
http://arxiv.org/abs/2206.10034
Research in the past several years has boosted the performance of automatic speaker verification systems and countermeasure systems to deliver low Equal Error Rates (EERs) on each system. However, research on joint optimization of both systems is sti
Externí odkaz:
http://arxiv.org/abs/2203.06517
Voice assistants, such as smart speakers, have exploded in popularity. It is currently estimated that the smart speaker adoption rate has exceeded 35% in the US adult population. Manufacturers have integrated speaker identification technology, which
Externí odkaz:
http://arxiv.org/abs/2109.02774
An emerging trend in audio processing is capturing low-level speech representations from raw waveforms. These representations have shown promising results on a variety of tasks, such as speech recognition and speech separation. Compared to handcrafte
Externí odkaz:
http://arxiv.org/abs/2109.02773
Autor:
Agarwal, Mayank, Chakraborti, Tathagata, Fu, Quchen, Gros, David, Lin, Xi Victoria, Maene, Jaron, Talamadupula, Kartik, Teng, Zhongwei, White, Jules
The NLC2CMD Competition hosted at NeurIPS 2020 aimed to bring the power of natural language processing to the command line. Participants were tasked with building models that can transform descriptions of command line tasks in English to their Bash s
Externí odkaz:
http://arxiv.org/abs/2103.02523
A multi-stage transfer learning strategy for diagnosing a class of rare laryngeal movement disorders
Autor:
Yao, Yu, Powell, Maria, White, Jules, Feng, Jian, Fu, Quchen, Zhang, Peng, Schmidt, Douglas C.
Publikováno v:
In Computers in Biology and Medicine November 2023 166