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Large Language Models (LLMs) demonstrate significant potential in multi-agent negotiation tasks, yet evaluation in this domain remains challenging due to a lack of robust and generalizable benchmarks. Abdelnabi et al. (2024) introduce a…

机器学习 · 计算机科学 2026-02-24 Jorge Carrasco Pollo , Ioannis Kapetangeorgis , Joshua Rosenthal , John Hua Yao

Scaling language models with more data, compute and parameters has driven significant progress in natural language processing. For example, thanks to scaling, GPT-3 was able to achieve strong results on in-context learning tasks. However,…

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…

Large Language Models (LLMs) have been transformative. They are pre-trained foundational models that are self-supervised and can be adapted with fine tuning to a wide range of natural language tasks, each of which previously would have…

计算与语言 · 计算机科学 2023-02-22 Terrence Sejnowski

Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. In this paper, we systematically explore the abilities of…

计算与语言 · 计算机科学 2025-02-25 Menglong Cui , Pengzhi Gao , Wei Liu , Jian Luan , Bin Wang

Cybersecurity education is challenging and it is helpful for educators to understand Large Language Models' (LLMs') capabilities for supporting education. This study evaluates the effectiveness of LLMs in conducting a variety of penetration…

密码学与安全 · 计算机科学 2026-03-30 Martin Nizon-Deladoeuille , Brynjólfur Stefánsson , Helmut Neukirchen , Thomas Welsh

Recent advances in Large Language Models (LLMs) have presented new opportunities for integrating Artificial General Intelligence (AGI) into biological research and education. This study evaluated the capabilities of leading LLMs, including…

Educational materials such as survey articles in specialized fields like computer science traditionally require tremendous expert inputs and are therefore expensive to create and update. Recently, Large Language Models (LLMs) have achieved…

计算与语言 · 计算机科学 2024-05-24 Fan Gao , Hang Jiang , Rui Yang , Qingcheng Zeng , Jinghui Lu , Moritz Blum , Dairui Liu , Tianwei She , Yuang Jiang , Irene Li

Large language models (LLMs) have demonstrated impressive capabilities, but still suffer from inconsistency issues (e.g. LLMs can react differently to disturbances like rephrasing or inconsequential order change). In addition to these…

计算与语言 · 计算机科学 2024-06-19 Zhe Yang , Yichang Zhang , Tianyu Liu , Jian Yang , Junyang Lin , Chang Zhou , Zhifang Sui

We explore generating factual and accurate tables from the parametric knowledge of large language models (LLMs). While LLMs have demonstrated impressive capabilities in recreating knowledge bases and generating free-form text, we focus on…

计算与语言 · 计算机科学 2024-06-18 Yevgeni Berkovitch , Oren Glickman , Amit Somech , Tomer Wolfson

Providing effective feedback is important for student learning in programming problem-solving. In this sense, Large Language Models (LLMs) have emerged as potential tools to automate feedback generation. However, their reliability and…

软件工程 · 计算机科学 2025-03-20 Priscylla Silva , Evandro Costa

This paper investigates the strategic decision-making capabilities of three Large Language Models (LLMs): GPT-3.5, GPT-4, and LLaMa-2, within the framework of game theory. Utilizing four canonical two-player games -- Prisoner's Dilemma,…

计算机科学与博弈论 · 计算机科学 2023-09-13 Nunzio Lorè , Babak Heydari

Large Language Models (LLMs), such as GPT, are considered to learn the latent distributions within large-scale web-crawl datasets and accomplish natural language processing (NLP) tasks by predicting the next token. However, this mechanism…

计算与语言 · 计算机科学 2025-02-04 Kun-Peng Ning , Jia-Yu Yao , Yu-Yang Liu , Mu-Nan Ning , Li Yuan

The rapid advancement of large language models has opened new avenues for automating complex problem-solving tasks such as algorithmic coding and competitive programming. This paper introduces a novel evaluation technique, LLM-ProS, to…

计算与语言 · 计算机科学 2026-03-03 Md Sifat Hossain , Anika Tabassum , Md. Fahim Arefin , Tarannum Shaila Zaman

This paper studies recent developments in large language models' (LLM) abilities to pass assessments in introductory and intermediate Python programming courses at the postsecondary level. The emergence of ChatGPT resulted in heated debates…

计算机与社会 · 计算机科学 2023-10-05 Jaromir Savelka , Arav Agarwal , Marshall An , Chris Bogart , Majd Sakr

This study investigates the efficacy of large language models (LLMs) as tools for grading master-level student essays. Utilizing a sample of 60 essays in political science, the study compares the accuracy of grades suggested by the GPT-4…

综合经济学 · 经济学 2024-06-25 Magnus Lundgren

In recent times, substantial advancements have been witnessed in large language models (LLMs), exemplified by ChatGPT, showcasing remarkable proficiency across a range of complex tasks. However, many mainstream LLMs (e.g. LLaMA) are…

计算与语言 · 计算机科学 2024-01-15 Jun Zhao , Zhihao Zhang , Luhui Gao , Qi Zhang , Tao Gui , Xuanjing Huang

Can we leverage LLMs to model the process of discovering novel language model (LM) architectures? Inspired by real research, we propose a multi-agent LLM approach that simulates the conventional stages of research, from ideation and…

人工智能 · 计算机科学 2025-06-26 Junyan Cheng , Peter Clark , Kyle Richardson

The disruptive technology provided by large-scale pre-trained language models (LLMs) such as ChatGPT or GPT-4 has received significant attention in several application domains, often with an emphasis on high-level opportunities and…

人机交互 · 计算机科学 2023-06-27 Philippe J. Giabbanelli

With the increasing use of large language models (LLMs), ensuring reliable performance in diverse, real-world environments is essential. Despite their remarkable achievements, LLMs often struggle with adversarial inputs, significantly…

计算与语言 · 计算机科学 2024-06-18 Yuqing Wang , Yun Zhao
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