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This paper examines the comparative effectiveness of a specialized compiled language model and a general-purpose model like OpenAI's GPT-3.5 in detecting SDGs within text data. It presents a critical review of Large Language Models (LLMs),…

计算与语言 · 计算机科学 2023-07-31 Arash Hajikhani , Carolyn Cole

This paper explores the automatic classification of exam questions and learning outcomes according to Bloom's Taxonomy. A small dataset of 600 sentences labeled with six cognitive categories - Knowledge, Comprehension, Application,…

计算与语言 · 计算机科学 2025-11-17 Ramya Kumar , Dhruv Gulwani , Sonit Singh

This pilot study presents a small-scale but carefully annotated benchmark of Named Entity Recognition (NER) performance across six systems: three non-LLM NLP tools (NLTK, spaCy, Stanza) and three general-purpose large language models (LLMs:…

计算与语言 · 计算机科学 2025-09-16 Payam Latifi

Instruction tuning large language models (LLMs) remains a challenging task, owing to the complexity of hyperparameter selection and the difficulty involved in evaluating the tuned models. To determine the optimal hyperparameters, an…

Although both Google Gemini (1.5 Flash) and ChatGPT (4o and 4o-mini) give research quality evaluation scores that correlate positively with expert scores in nearly all fields, and more strongly that citations in most, it is not known…

数字图书馆 · 计算机科学 2025-08-12 Mike Thelwall

Big Language Models (LLMs) are changing the way businesses use software, the way people live their lives and the way industries work. Companies like Google, High-Flyer, Anthropic, OpenAI and Meta are making better LLMs. So, it's crucial to…

人工智能 · 计算机科学 2025-10-28 Urja Kohli , Aditi Singh , Arun Sharma

The rapid emergence of large language models (LLMs) has raised urgent questions across the modern workforce about this new technology's strengths, weaknesses, and capabilities. For privacy professionals, the question is whether these AI…

计算机与社会 · 计算机科学 2025-08-13 Zane Witherspoon , Thet Mon Aye , YingYing Hao

This study evaluates the capabilities of Multimodal Large Language Models (LLMs) and Vision Language Models (VLMs) in the task of single-label classification of Christian Iconography. The goal was to assess whether general-purpose VLMs…

计算机视觉与模式识别 · 计算机科学 2025-09-24 Gianmarco Spinaci , Lukas Klic , Giovanni Colavizza

This study presents a comprehensive comparative evaluation of four state-of-the-art Large Language Models (LLMs)--Claude 3.7 Sonnet, DeepSeek-V3, Gemini 2.0 Flash, and GPT-4o--for sentiment analysis and emotion detection in Persian social…

计算与语言 · 计算机科学 2025-09-19 Kian Tohidi , Kia Dashtipour , Simone Rebora , Sevda Pourfaramarz

The legal landscape encompasses a wide array of lawsuit types, presenting lawyers with challenges in delivering timely and accurate information to clients, particularly concerning critical aspects like potential imprisonment duration or…

人工智能 · 计算机科学 2024-07-30 Jia-Hong Huang , Chao-Chun Yang , Yixian Shen , Alessio M. Pacces , Evangelos Kanoulas

Security analysts face increasing pressure to triage large and complex vulnerability backlogs. Large Language Models (LLMs) offer a potential aid by automating parts of the interpretation process. We evaluate four models (ChatGPT, Claude,…

密码学与安全 · 计算机科学 2025-10-22 Osama Al Haddad , Muhammad Ikram , Ejaz Ahmed , Young Lee

The ability to rigorously estimate the failure rates of large language models (LLMs) is a prerequisite for their safe deployment. Currently, however, practitioners often face a tradeoff between expensive human gold standards and potentially…

计算与语言 · 计算机科学 2026-04-07 Minghe Shen , Ananth Balashankar , Adam Fisch , David Madras , Miguel Rodrigues

In the realm of artificial intelligence, where a vast majority of data is unstructured, obtaining substantial amounts of labeled data to train supervised machine learning models poses a significant challenge. To address this, we delve into…

机器学习 · 计算机科学 2024-01-19 Natan Vidra , Thomas Clifford , Katherine Jijo , Eden Chung , Liang Zhang

Large language models (LLMs) have demonstrated capabilities across diverse domains, yet their performance on rare disease diagnosis from narrative medical cases remains underexplored. We introduce a novel dataset of 176 symptom-diagnosis…

计算与语言 · 计算机科学 2025-11-17 Arsh Gupta , Ajay Narayanan Sridhar , Bonam Mingole , Amulya Yadav

Data imputation is a cornerstone technique for handling missing values in real-world datasets, which are often plagued by missingness. Despite recent progress, prior studies on Large Language Models-based imputation remain limited by…

Artificial Intelligence techniques such as Machine Learning (ML) have not been exploited to their maximum potential in the legal domain. This has been partially due to the insufficient explanations they provided about their decisions.…

Unlocking the potential of Large Language Models (LLMs) in data classification represents a promising frontier in natural language processing. In this work, we evaluate the performance of different LLMs in comparison with state-of-the-art…

计算与语言 · 计算机科学 2025-01-16 Arina Kostina , Marios D. Dikaiakos , Dimosthenis Stefanidis , George Pallis

In this paper, we assess the visualization literacy of two prominent Large Language Models (LLMs): OpenAI's Generative Pretrained Transformers (GPT), the backend of ChatGPT, and Google's Gemini, previously known as Bard, to establish…

性能 · 计算机科学 2025-01-28 Jiayi Hong , Christian Seto , Arlen Fan , Ross Maciejewski

Large Language Models (LLMs) have shown impressive performance on a range of educational tasks, but are still understudied for their potential to solve mathematical problems. In this study, we compare three prominent LLMs, including GPT-4o,…

人工智能 · 计算机科学 2025-07-01 Ruonan Wang , Runxi Wang , Yunwen Shen , Chengfeng Wu , Qinglin Zhou , Rohitash Chandra

Large language models (LLMs) have demonstrated great potential for domain-specific applications, such as the law domain. However, recent disputes over GPT-4's law evaluation raise questions concerning their performance in real-world legal…

计算与语言 · 计算机科学 2023-10-19 Ruihao Shui , Yixin Cao , Xiang Wang , Tat-Seng Chua