Large language models pose unique testing challenges due to their free-form textual outputs. Using a combination of similarity testing, column coverage validation, exact match, visual output screening, and even LLM-based evaluation, we can rigorously assess LLMs along multiple dimensions. A ...
Testing Large Language Models with Natural Language Requirements 主讲人(Speaker):Xueqing Liu 时间(Date & Time):2023.12.19;1-2pm 地点(Location):理科一号楼1621(燕园校区)Room 1621, Science Building #1 (Yanyuan) 邀请人(Host):谢涛 主办...
This is the official repo for the paper Testing Large Language Models for Physics Knowledge Large Language Models (LLMs) have gained significant popularity in recent years for their ability to answer questions in various fields. However, these models have a tendency to "hallucinate" their responses...
The recent rise of large language models (LLMs), such as generative pre-trained transformer (GPT) models, has shown some promise that artificial theory of mind may not be too distant an idea. Generative LLMs exhibit performance that is characteristic of sophisticated decision-making and reasoning...
At the core of what defines us as humans is the concept of theory of mind: the ability to track other people’s mental states. The recent development of large language models (LLMs) such as ChatGPT has led to intense debate about the possibility that the
Large language models (LLMs) are advanced deep learning algorithms that can process written or spoken prompts and generate texts in response to these prompts. These models have recently become increasingly popular and are now helping many users to create summaries of long documents, gain inspiration...
· Proj CDeepFuzz Paper Reading: Large Language Models are Zero-Shot Fuzzers:Fuzzing Deep-Learning Libraries via Large Language Models · Proj CDeepFuzz Paper Reading: Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT · 大模型评测-微软亚洲研究院:A Surv...
Large Language Models (LLMs) have demonstrated exceptional capabilities in various software engineering and coding tasks. However, their application in the field of compilers has not been fully explored. Meta’s recently released Meta Large Language Model Compiler provides a new means for compi...
Large language models (LLMs) are ML models trained on extensive data corpora, enabling them to perform multiple downstream ML tasks. Consequently, using LLMs allows the ML solution developer to jumpstart the solution construction by starting with one or more LLMs. This chapter discusses the ...
Artificial intelligence-based large language models (LLMs) have the potential to substantially improve the efficiency and scale of ecological research, but their propensity for delivering incorrect information raises significant concern about their usefu