Section 5. Docstring Generation 还是采用Section 4中的数据集,我们训练了一个新的模型Codex-D,在给定code的情况下,生成对应的docstring。为了评估该模型的效果,我们采用了人工评估的方式——每个problem,生成10个docstring,然后人工标注。效果如下: Section 6. Limitations 训练
最后,扩展了代码生成模型的更广泛影响,并讨论了模型的局限性,找到了很大的改进空间。 参考文献 Chen M, Tworek J, Jun H, et al. Evaluating large language models trained on code[J]. arXiv preprint arXiv:2107.03374, 2021. 发布于 2023-04-06 21:33・广东...
OpenAI Codex Software & Engineering Transformers Compute Scaling Language Generative Models Authors Mark Chen,Jerry Tworek,Heewoo Jun,Qiming Yuan,Henrique Pondé,Jared Kaplan,Harri Edwards,Yura Burda,Nicholas Joseph,Greg Brockman,Alex Ray,Raul Puri,Gretchen Krueger,Michael Petrov,Heidy Khlaaf ...
Recent advances in large language models (LLMs) have demonstrated remarkable successes in zero- and few-shot performance on various downstream tasks, paving the way for applications in high-stakes domains. In this study, we systematically examine the capabilities and limitations of LLMs, specifically...
evaluating large language models trained on code顺理成章的,把模型做的再大一点,训练数据集做的再大一些,计算资源再多一些,就可以生成更长的代码。这篇文章做的事情就是把GPT模型应用在代码生成上,具体来说输入函数的签名和注释(prompt),告诉模型这个函数要做什么事情,然后模型输出实现代码。 这里有三个示例,...
This is an evaluation harness for the HumanEval problem solving dataset described in the paper "Evaluating Large Language Models Trained on Code". Installation Make sure to use python 3.7 or later: $ conda create -n codex python=3.7 $ conda activate codex ...
This study explores the use of Large Language Models (LLMs), specifically GPT-4, in analysing classroom dialogue—a key task for teaching diagnosis and quality improvement. Traditional qualitative methods are both knowledge- and labour-intensive. This research investigates the potential of LLMs to ...
LongICLBench Benchmark: Evaluating Large Language Models on Long In-Context Learning for Extreme-Label Classification
As large language models (LLMs) constantly evolve, ensuring their safety remains a critical research problem. Previous red-teaming approaches for LLM safety have primarily focused on single prompt attacks or goal hijacking. To the best of our knowledge, we are the first to study LLM safety in ...
Large Language Models (LLMs) are extensively used today across various sectors, including academia, research, business, and finance, for tasks such as text generation, summarization, and translation. Despite their widespread adoption, these models often produce incorrect and misleading information, ...