Evaluating Large Language Models Trained on Code

Language Models of Code are Few-Shot Commonsense Learners

Evaluating large language models trained · on code. arXiv preprint arXiv:2107.03374. Aakanksha Chowdhery, Sharan Narang, Jacob Devlin,. Maarten Bosma, Gaurav ...

Evaluating large language models in theory of mind tasks - PNAS

Our results show that recent large language models (LLMs) can solve false-belief tasks, typically used to evaluate ToM in humans.

Evaluating Large Language Models: Methods, Best Practices & Tools

Perplexity. One of the crucial metrics used to evaluate Large Language Models efficacy is 'perplexity.' In essence, perplexity measures the ...

A bilingual benchmark for evaluating large language models - PeerJ

This work introduces a new benchmark for the bilingual evaluation of large language models (LLMs) in English and Arabic.

Open-Sourced Training Datasets for Large Language Models (LLMs)

As popular as they are, large language models rely on the training datasets they learn on. LLMs consist of multiple hidden layers of deep neural networks, which ...

Framework for evaluating code generation ability of large language ...

AbstractLarge language models (LLMs) have revolutionized various applications in natural language processing and exhibited proficiency in generating ...

Evaluating Large Language Models Trained on Code | BibSonomy

We introduce Codex, a GPT language model fine-tuned on publicly available code from GitHub, and study its Python code-writing capabilities.

Evaluating large language models' ability to generate interpretive ...

We collected and evaluated arguments from both human annotators and state-of-the-art generative language models in order to determine the ...

Evaluating Large Language Models for Software Testing

Large language models (LLMs) have demonstrated significant prowess in code analysis and natural language processing, making them highly valuable ...

Unveiling the Power of Code: Evaluating Large Language Models

We will discuss its background, explore the extension of language modeling to different data domains, and Delve into the human evaluation ...

Evaluating Large Language Models for Verilog Code Generation

We also demonstrate that the Verilog code generation capability of pretrained language models could be improved with supervised fine-tuning ...

Evaluation of Large Language Models on Code Obfuscation ...

These pieces of code were included to lower the likelihood of the LLMs having encountered them during training. We used obfuscations with varying complexity.

Code Evaluation - a Vipitis Collection - Hugging Face

Code Evaluation · Evaluating Large Language Models Trained on Code · CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation · Out of ...

Evaluating Large Language Models: A Complete Guide - SingleStore

LLM evaluation is key to understanding how well an LLM performs. It helps developers identify the model's strengths and weaknesses, ensuring it functions ...

On the malicious use of large language models like GPT-3

Language models are made better at generating code when fine-tuned to do so. Regular GPT models which have not specifically been trained on code ...

Testing and Evaluating Large Language Models in AI Applications

A guide to evaluating and testing large language models. Learn how to test your system prompts and evaluate your AI's performance.

LLMSecCode: Evaluating Large Language Models for Secure Coding

Large language models (LLMs) are powerful AI systems that can generate human-like text, including computer code. The researchers behind this ...

COS 597G: Understanding Large Language Models

Train or fine-tune a medium-sized language model (e.g., BERT/RoBERTa, T5, GPT-2) yourself for the task of your interest. You will probably need to access pre- ...

Large Language Models Are Poor Medical Coders - NEJM AI

Large language models (LLMs) are deep learning models trained on extensive textual data, capable of generating text output. ... LLMs have shown ...

CodeT5: The Code-aware Encoder-Decoder based Pre-trained ...

Chen et al. 2021. Evaluating large language models trained on code. CoRR, abs/2107.03374.