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While large language models (LLMs) achieve near-perfect scores on medical licensing exams, these evaluations inadequately reflect the complexity and diversity of real-world clinical practice. We introduce MedHELM, an extensible evaluation…

This article presents a comprehensive review of the challenges associated with using massive web-mined corpora for the pre-training of large language models (LLMs). This review identifies key challenges in this domain, including challenges…

计算与语言 · 计算机科学 2024-07-11 Michał Perełkiewicz , Rafał Poświata

The rapid rise in popularity of Large Language Models (LLMs) with emerging capabilities has spurred public curiosity to evaluate and compare different LLMs, leading many researchers to propose their own LLM benchmarks. Noticing preliminary…

人工智能 · 计算机科学 2025-05-15 Timothy R. McIntosh , Teo Susnjak , Nalin Arachchilage , Tong Liu , Paul Watters , Malka N. Halgamuge

The pervasive influence of social media during the COVID-19 pandemic has been a double-edged sword, enhancing communication while simultaneously propagating misinformation. This \textit{Digital Infodemic} has highlighted the urgent need for…

计算与语言 · 计算机科学 2024-12-24 Tanjim Bin Faruk

The proliferation of open-source Large Language Models (LLMs) from various institutions has highlighted the urgent need for comprehensive evaluation methods. However, current evaluation platforms, such as the widely recognized HuggingFace…

计算与语言 · 计算机科学 2024-11-01 Fanghua Ye , Mingming Yang , Jianhui Pang , Longyue Wang , Derek F. Wong , Emine Yilmaz , Shuming Shi , Zhaopeng Tu

The development of highly fluent large language models (LLMs) has prompted increased interest in assessing their reasoning and problem-solving capabilities. We investigate whether several LLMs can solve a classic type of deductive reasoning…

计算与语言 · 计算机科学 2024-04-16 Spencer M. Seals , Valerie L. Shalin

Large Language Models (LLMs) have demonstrated exceptional natural language understanding abilities and have excelled in a variety of natural language processing (NLP)tasks in recent years. Despite the fact that most LLMs are trained…

计算与语言 · 计算机科学 2023-10-25 Xiang Zhang , Senyu Li , Bradley Hauer , Ning Shi , Grzegorz Kondrak

Large Language Models (LLMs) have demonstrated remarkable instruction-following capabilities across various applications. However, their performance in multilingual settings lacks systematic investigation, with existing evaluations lacking…

计算与语言 · 计算机科学 2025-11-04 Zhenyu Li , Kehai Chen , Yunfei Long , Xuefeng Bai , Yaoyin Zhang , Xuchen Wei , Juntao Li , Min Zhang

Vision-language models are integral to computer vision research, yet many high-performing models remain closed-source, obscuring their data, design and training recipe. The research community has responded by using distillation from…

Analyzing vast textual data and summarizing key information from electronic health records imposes a substantial burden on how clinicians allocate their time. Although large language models (LLMs) have shown promise in natural language…

Artificial intelligence (AI) technology has advanced rapidly in recent years, with large language models (LLMs) emerging as a significant breakthrough. LLMs are increasingly making an impact across various industries, with the medical field…

人工智能 · 计算机科学 2025-09-24 Zhiyu Kan , Wensheng Gan , Zhenlian Qi , Philip S. Yu

Objective This study is part of a series of initiatives at a UK university designed to cultivate a deep understanding of students' perspectives on analytics that resonate with their unique learning needs. It explores collaborative data…

计算机与社会 · 计算机科学 2025-02-18 Raghda Zahran , Jianfei Xu , Huizhi Liang , Matthew Forshaw

The evaluation of Large Language Models (LLMs) on mathematical reasoning has largely focused on elementary problems, competition-style questions, or formal theorem proving, leaving graduate-level and computational mathematics relatively…

计算与语言 · 计算机科学 2026-03-05 Bianca Raimondi , Francesco Pivi , Davide Evangelista , Maurizio Gabbrielli

Large language models (LLMs) are increasingly being deployed across disciplines due to their advanced reasoning and problem solving capabilities. To measure their effectiveness, various benchmarks have been developed that measure aspects of…

Large Language Models (LLMs) are at the forefront of NLP achievements but fall short in dealing with shortcut learning, factual inconsistency, and vulnerability to adversarial inputs.These shortcomings are especially critical in medical…

计算与语言 · 计算机科学 2024-04-09 Mael Jullien , Marco Valentino , André Freitas

The progress of Large Language Models (LLMs) like ChatGPT raises the question of how they can be integrated into education. One hope is that they can support mathematics learning, including word-problem solving. Since LLMs can handle…

计算与语言 · 计算机科学 2025-08-12 Anselm R. Strohmaier , Wim Van Dooren , Kathrin Seßler , Brian Greer , Lieven Verschaffel

Despite the rapid expansion of Large Language Models (LLMs) in healthcare, robust and explainable evaluation of their ability to assess clinical trial reporting according to CONSORT standards remains an open challenge. In particular,…

人工智能 · 计算机科学 2026-02-26 Sohyeon Jeon , Hyung-Chul Lee

The impressive essay writing and problem-solving capabilities of large language models (LLMs) like OpenAI's ChatGPT have opened up new avenues in education. Our goal is to gain insights into the widespread use of LLMs among secondary…

人机交互 · 计算机科学 2024-12-02 Tiffany Zhu , Kexun Zhang , William Yang Wang

Large Language Models(LLMs)have become effective tools for natural language processing and have been used in many different fields. This essay offers a succinct summary of various LLM subcategories. The survey emphasizes recent developments…

计算与语言 · 计算机科学 2023-07-21 Saurabh Pahune , Manoj Chandrasekharan

Multimodal large language models (MLLMs) demonstrate impressive performance on scientific reasoning tasks (e.g., ScienceQA). However, most existing benchmarks focus narrowly on the accuracy of the final answer while ignoring other metrics.…

计算与语言 · 计算机科学 2025-05-13 Ming Liu , Liwen Wang , Wensheng Zhang
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