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To thoroughly assess the mathematical reasoning abilities of Large Language Models (LLMs), we need to carefully curate evaluation datasets covering diverse mathematical concepts and mathematical problems at different difficulty levels. In…

计算与语言 · 计算机科学 2024-09-09 Yan Liu , Renren Jin , Ling Shi , Zheng Yao , Deyi Xiong

Due to the rapid advancements in multimodal large language models, evaluating their multimodal mathematical capabilities continues to receive wide attention. Despite the datasets like MathVista proposed benchmarks for assessing mathematical…

Large language models (LLMs) have obtained promising results in mathematical reasoning, which is a foundational skill for human intelligence. Most previous studies focus on improving and measuring the performance of LLMs based on textual…

计算与语言 · 计算机科学 2024-11-04 Wentao Liu , Qianjun Pan , Yi Zhang , Zhuo Liu , Ji Wu , Jie Zhou , Aimin Zhou , Qin Chen , Bo Jiang , Liang He

Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address…

As the capabilities of large language models (LLMs) continue to advance, evaluating their performance becomes increasingly crucial and challenging. This paper aims to bridge this gap by introducing CMMLU, a comprehensive Chinese benchmark…

计算与语言 · 计算机科学 2024-01-19 Haonan Li , Yixuan Zhang , Fajri Koto , Yifei Yang , Hai Zhao , Yeyun Gong , Nan Duan , Timothy Baldwin

With the accelerating development of Large Language Models (LLMs), many LLMs are beginning to be used in the Chinese K-12 education domain. The integration of LLMs and education is getting closer and closer, however, there is currently no…

计算与语言 · 计算机科学 2024-01-30 Jinchang Hou , Chang Ao , Haihong Wu , Xiangtao Kong , Zhigang Zheng , Daijia Tang , Chengming Li , Xiping Hu , Ruifeng Xu , Shiwen Ni , Min Yang

Purpose: The rapid emergence of large language models (LLMs) such as ChatGPT has significantly impacted foreign language education, yet their pedagogical grammar competence remains under-assessed. This paper introduces CPG-EVAL, the first…

计算与语言 · 计算机科学 2025-04-21 Dong Wang

Large Language Models (LLMs) have demonstrated exceptional capabilities in various natural language tasks, often achieving performances that surpass those of humans. Despite these advancements, the domain of mathematics presents a…

计算与语言 · 计算机科学 2024-04-02 Ankit Satpute , Noah Giessing , Andre Greiner-Petter , Moritz Schubotz , Olaf Teschke , Akiko Aizawa , Bela Gipp

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

This study systematically evaluated the mathematical reasoning capabilities of Large Language Models (LLMs) using the 2026 Korean College Scholastic Ability Test (CSAT) Mathematics section, ensuring a completely contamination-free…

计算与语言 · 计算机科学 2025-12-02 Goun Pyeon , Inbum Heo , Jeesu Jung , Taewook Hwang , Hyuk Namgoong , Hyein Seo , Yerim Han , Eunbin Kim , Hyeonseok Kang , Sangkeun Jung

New NLP benchmarks are urgently needed to align with the rapid development of large language models (LLMs). We present C-Eval, the first comprehensive Chinese evaluation suite designed to assess advanced knowledge and reasoning abilities of…

Large language models (LLMs) demonstrate impressive capabilities in mathematical reasoning. However, despite these achievements, current evaluations are mostly limited to specific mathematical topics, and it remains unclear whether LLMs are…

计算与语言 · 计算机科学 2025-04-01 Arash Gholami Davoodi , Seyed Pouyan Mousavi Davoudi , Pouya Pezeshkpour

Large-scale language models (LLMs) has shown remarkable capability in various of Natural Language Processing (NLP) tasks and attracted lots of attention recently. However, some studies indicated that large language models fail to achieve…

计算与语言 · 计算机科学 2025-03-18 Fanyi Qu , Chenming Tang , Yunfang Wu

The performance of large language models (LLMs) on existing reasoning benchmarks has significantly improved over the past years. In response, we present JEEBench, a considerably more challenging benchmark dataset for evaluating the problem…

计算与语言 · 计算机科学 2023-10-24 Daman Arora , Himanshu Gaurav Singh , Mausam

This study explores the application of Large Language Models (LLMs), specifically GPT-4, in the analysis of classroom dialogue, a crucial research task for both teaching diagnosis and quality improvement. Recognizing the knowledge-intensive…

计算与语言 · 计算机科学 2024-10-08 Yun Long , Haifeng Luo , Yu Zhang

With the rapid popularity of large language models such as ChatGPT and GPT-4, a growing amount of attention is paid to their safety concerns. These models may generate insulting and discriminatory content, reflect incorrect social values,…

计算与语言 · 计算机科学 2023-04-21 Hao Sun , Zhexin Zhang , Jiawen Deng , Jiale Cheng , Minlie Huang

Large language models (LLMs) are increasingly applied in computer science education for tasks such as tutoring, content generation, and code assessment. However, systematic evaluations aligned with formal curricula and certification…

Large Language Models (LLMs) have tremendous potential to play a key role in supporting mathematical reasoning, with growing use in education and AI research. However, most existing benchmarks are limited to English, creating a significant…

计算机与社会 · 计算机科学 2025-10-16 Tabia Tanzin Prama , Christopher M. Danforth , Peter Sheridan Dodds

Recent advances in large language models (LLMs) have led to substantial progress in domain-specific applications, particularly within the legal domain. However, general-purpose models such as GPT-4 often struggle with specialized subdomains…

人工智能 · 计算机科学 2026-01-16 Zixun Lan , Maochun Xu , Yifan Ren , Rui Wu , Jianghui Zhou , Xueyang Cheng , Jianan Ding Ding , Xinheng Wang , Mingmin Chi , Fei Ma

This study is a pioneering endeavor to investigate the capabilities of Large Language Models (LLMs) in addressing conceptual questions within the domain of mechanical engineering with a focus on mechanics. Our examination involves a…

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