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This study critically evaluates the efficacy of prompting methods in enhancing the mathematical reasoning capability of large language models (LLMs). The investigation uses three prescriptive prompting methods - simple, persona, and…

Thematic analysis and other variants of inductive coding are widely used qualitative analytic methods within empirical legal studies (ELS). We propose a novel framework facilitating effective collaboration of a legal expert with a large…

Artificial Intelligence · Computer Science 2023-10-31 Jakub Drápal , Hannes Westermann , Jaromir Savelka

This paper aims to efficiently enable Large Language Models (LLMs) to use multimodal tools. Advanced proprietary LLMs, such as ChatGPT and GPT-4, have shown great potential for tool usage through sophisticated prompt engineering.…

Computer Vision and Pattern Recognition · Computer Science 2023-05-31 Rui Yang , Lin Song , Yanwei Li , Sijie Zhao , Yixiao Ge , Xiu Li , Ying Shan

It has been suggested that large language models such as GPT-4 have acquired some form of understanding beyond the correlations among the words in text including some understanding of mathematics as well. Here, we perform a critical inquiry…

Machine Learning · Computer Science 2023-11-15 Roozbeh Yousefzadeh , Xuenan Cao

Large Language Models (LLMs) such as GPT-4 have shown enough promise in the few-shot learning context to suggest use in the generation of "silver" data and refinement of new ontologies through iterative application and review. Such…

Artificial Intelligence · Computer Science 2024-08-05 Steven Fincke , Adrien Bibal , Elizabeth Boschee

In this study, we evaluated the capability of Large Language Models (LLMs), particularly OpenAI's GPT-4, in detecting software vulnerabilities, comparing their performance against traditional static code analyzers like Snyk and Fortify. Our…

Software Engineering · Computer Science 2023-08-22 David Noever

Pretrained large language models (LLMs) are widely used in many sub-fields of natural language processing (NLP) and generally known as excellent few-shot learners with task-specific exemplars. Notably, chain of thought (CoT) prompting, a…

Computation and Language · Computer Science 2023-01-31 Takeshi Kojima , Shixiang Shane Gu , Machel Reid , Yutaka Matsuo , Yusuke Iwasawa

The latest paradigm shift in software development brings in the innovation and automation afforded by Large Language Models (LLMs), showcased by Generative Pre-trained Transformer (GPT), which has shown remarkable capacity to generate code…

Software Engineering · Computer Science 2024-06-12 Xiaoyin Wang , Dakai Zhu

OpenAI's latest large vision-language model (LVLM), GPT-4V(ision), has piqued considerable interest for its potential in medical applications. Despite its promise, recent studies and internal reviews highlight its underperformance in…

Computation and Language · Computer Science 2023-12-13 Pengcheng Chen , Ziyan Huang , Zhongying Deng , Tianbin Li , Yanzhou Su , Haoyu Wang , Jin Ye , Yu Qiao , Junjun He

Large Language Models (LLMs) have demonstrated impressive zero shot performance on a wide range of NLP tasks, demonstrating the ability to reason and apply commonsense. A relevant application is to use them for creating high quality…

Computation and Language · Computer Science 2024-07-11 Vinay Samuel , Houda Aynaou , Arijit Ghosh Chowdhury , Karthik Venkat Ramanan , Aman Chadha

Recently, with the chain of thought (CoT) prompting, large language models (LLMs), e.g., GPT-3, have shown strong reasoning ability in several natural language processing tasks such as arithmetic, commonsense, and logical reasoning.…

Artificial Intelligence · Computer Science 2023-10-20 Yixuan Weng , Minjun Zhu , Fei Xia , Bin Li , Shizhu He , Shengping Liu , Bin Sun , Kang Liu , Jun Zhao

In the rapidly evolving field of natural language processing, the translation of linguistic descriptions into mathematical formulation of optimization problems presents a formidable challenge, demanding intricate understanding and…

Computation and Language · Computer Science 2024-03-05 Tasnim Ahmed , Salimur Choudhury

Background and Context: Over the past year, large language models (LLMs) have taken the world by storm. In computing education, like in other walks of life, many opportunities and threats have emerged as a consequence. Objectives: In this…

Computers and Society · Computer Science 2023-06-12 Arto Hellas , Juho Leinonen , Sami Sarsa , Charles Koutcheme , Lilja Kujanpää , Juha Sorva

This study aims to explore the best practices for utilizing GenAI as a programming tool, through a comparative analysis between GPT-4 and GLM-4. By evaluating prompting strategies at different levels of complexity, we identify that simplest…

Software Engineering · Computer Science 2024-02-21 Angus Yang , Zehan Li , Jie Li

Large Language Models (LLMs) have demonstrated remarkable performance across diverse tasks and exhibited impressive reasoning abilities by applying zero-shot Chain-of-Thought (CoT) prompting. However, due to the evolving nature of sentence…

Computation and Language · Computer Science 2024-02-09 Feihu Jin , Yifan Liu , Ying Tan

The challenges of solving complex university-level mathematics problems, particularly those from MIT, and Columbia University courses, and selected tasks from the MATH dataset, remain a significant obstacle in the field of artificial…

Computation and Language · Computer Science 2025-09-23 Eishkaran Singh , Tanav Singh Bajaj , Siddharth Nayak

This paper does not present a novel method. Instead, it delves into an essential, yet must-know baseline in light of the latest advancements in Generative Artificial Intelligence (GenAI): the utilization of GPT-4 for visual understanding.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Wenhao Wu , Huanjin Yao , Mengxi Zhang , Yuxin Song , Wanli Ouyang , Jingdong Wang

Lately, Large Language Models have been widely used in code generation. GPT4 is considered the most potent Large Language Model from Openai. In this paper, we examine GPT3.5 and GPT4 as coding assistants. More specifically, we have…

Artificial Intelligence · Computer Science 2023-09-25 Lefteris Moussiades , George Zografos

Large Language Models (LLMs) have recently achieved impressive performance in math and reasoning benchmarks. However, they often struggle with logic problems and puzzles that are relatively easy for humans. To further investigate this, we…

Artificial Intelligence · Computer Science 2025-09-16 Nasim Borazjanizadeh , Roei Herzig , Trevor Darrell , Rogerio Feris , Leonid Karlinsky

To support software developers in understanding and maintaining programs, various automatic (source) code summarization techniques have been proposed to generate a concise natural language summary (i.e., comment) for a given code snippet.…

Software Engineering · Computer Science 2025-08-26 Weisong Sun , Yun Miao , Yuekang Li , Hongyu Zhang , Chunrong Fang , Yi Liu , Gelei Deng , Yang Liu , Zhenyu Chen