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Large language models have emerged abilities including chain-of-thought to answer math word problems step by step. Solving math word problems not only requires abilities to disassemble problems via chain-of-thought but also needs to…

Computation and Language · Computer Science 2023-04-06 Zheng Yuan , Hongyi Yuan , Chuanqi Tan , Wei Wang , Songfang Huang

Large language models (LLMs) have demonstrated significant potential in the realm of natural language understanding and programming code processing tasks. Their capacity to comprehend and generate human-like code has spurred research into…

Software Engineering · Computer Science 2024-03-07 Chongzhou Fang , Ning Miao , Shaurya Srivastav , Jialin Liu , Ruoyu Zhang , Ruijie Fang , Asmita , Ryan Tsang , Najmeh Nazari , Han Wang , Houman Homayoun

Ensuring data quality in large tabular datasets is a critical challenge, typically addressed through data wrangling tasks. Traditional statistical methods, though efficient, cannot often understand the semantic context and deep learning…

Machine Learning · Computer Science 2025-02-25 Ashlesha Akella , Krishnasuri Narayanam

Large Language Models (LLMs), typified by OpenAI's GPT, have marked a significant advancement in artificial intelligence. Trained on vast amounts of text data, LLMs are capable of understanding and generating human-like text across a…

Artificial Intelligence · Computer Science 2024-10-29 Haochen Zhang , Yuyang Dong , Chuan Xiao , Masafumi Oyamada

Large Language Models offer new opportunities to devise automated implementation generation methods that can tackle problem solving activities beyond traditional methods, which require algorithmic specifications and can use only static…

Computation and Language · Computer Science 2025-01-06 Hashmath Shaik , Alex Doboli

This paper looks at the ability of large language models to participate in educational guided reading. We specifically, evaluate their ability to generate meaningful questions from the input text, generate diverse questions both in terms of…

Computation and Language · Computer Science 2023-05-22 Peter Ochieng

Large Language Models (LLMs), originally developed for natural language processing (NLP), have demonstrated the potential to generalize across modalities and domains. With their in-context learning (ICL) capabilities, LLMs can perform…

Artificial Intelligence · Computer Science 2025-08-26 Nikolaos Pavlidis , Vasilis Perifanis , Symeon Symeonidis , Pavlos S. Efraimidis

High-quality textual training data is essential for the success of multimodal data processing tasks, yet outputs from image captioning models like BLIP and GIT often contain errors and anomalies that are difficult to rectify using…

Computation and Language · Computer Science 2025-02-25 Elyas Meguellati , Nardiena Pratama , Shazia Sadiq , Gianluca Demartini

Data plays a fundamental role in training Large Language Models (LLMs). Efficient data management, particularly in formulating a well-suited training dataset, is significant for enhancing model performance and improving training efficiency…

Computation and Language · Computer Science 2024-08-05 Zige Wang , Wanjun Zhong , Yufei Wang , Qi Zhu , Fei Mi , Baojun Wang , Lifeng Shang , Xin Jiang , Qun Liu

Large language models (LLMs) have shown to be valuable tools for tackling process mining tasks. Existing studies report on their capability to support various data-driven process analyses and even, to some extent, that they are able to…

Databases · Computer Science 2025-05-01 Adrian Rebmann , Fabian David Schmidt , Goran Glavaš , Han van der Aa

By virtue of its great utility in solving real-world problems, optimization modeling has been widely employed for optimal decision-making across various sectors, but it requires substantial expertise from operations research professionals.…

The advent of large language models marks a revolutionary breakthrough in artificial intelligence. With the unprecedented scale of training and model parameters, the capability of large language models has been dramatically improved,…

Information Retrieval · Computer Science 2025-01-16 Jin Chen , Zheng Liu , Xu Huang , Chenwang Wu , Qi Liu , Gangwei Jiang , Yuanhao Pu , Yuxuan Lei , Xiaolong Chen , Xingmei Wang , Defu Lian , Enhong Chen

Large Language Models (LLMs) have demonstrated remarkable capabilities in important tasks such as natural language understanding and language generation, and thus have the potential to make a substantial impact on our society. Such…

Computation and Language · Computer Science 2024-05-24 Zhongwei Wan , Xin Wang , Che Liu , Samiul Alam , Yu Zheng , Jiachen Liu , Zhongnan Qu , Shen Yan , Yi Zhu , Quanlu Zhang , Mosharaf Chowdhury , Mi Zhang

This study investigates how Large Language Models (LLMs) leverage source and reference data in machine translation evaluation task, aiming to better understand the mechanisms behind their remarkable performance in this task. We design the…

Computation and Language · Computer Science 2024-06-07 Xu Huang , Zhirui Zhang , Xiang Geng , Yichao Du , Jiajun Chen , Shujian Huang

Recently, Large Language Models (LLMs) have drawn significant attention due to their outstanding reasoning capabilities and extensive knowledge repository, positioning them as superior in handling various natural language processing tasks…

Computation and Language · Computer Science 2023-11-30 Han Cao , Lingwei Wei , Mengyang Chen , Wei Zhou , Songlin Hu

The rapid advancement of large language models, such as the Generative Pre-trained Transformer (GPT) series, has had significant implications across various disciplines. In this study, we investigate the potential of the state-of-the-art…

Computation and Language · Computer Science 2023-09-06 Yunhao Yang , Anshul Tomar

High-quality, error-free datasets are a key ingredient in building reliable, accurate, and unbiased machine learning (ML) models. However, real world datasets often suffer from errors due to sensor malfunctions, data entry mistakes, or…

Machine Learning · Computer Science 2025-03-11 Tommaso Bendinelli , Artur Dox , Christian Holz

Large Language Models (LLMs) have demonstrated their remarkable capabilities in numerous fields. This survey focuses on how LLMs empower users, regardless of their technical background, to use human languages to automatically generate…

Software Engineering · Computer Science 2025-04-03 Nam Huynh , Beiyu Lin

The increasing size and complexity of pre-trained language models have demonstrated superior performance in many applications, but they usually require large training datasets to be adequately trained. Insufficient training sets could…

Computation and Language · Computer Science 2025-02-03 Yaping Chai , Haoran Xie , Joe S. Qin

Large language models (LLMs) show best-in-class performance across a wide range of natural language processing applications. Training these models is an extremely computationally expensive task; frontier Artificial Intelligence (AI)…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-10-10 Alexander Interrante-Grant , Carla Varela-Rosa , Suhaas Narayan , Chris Connelly , Albert Reuther