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Intrigued by the claims of emergent reasoning capabilities in LLMs trained on general web corpora, in this paper, we set out to investigate their planning capabilities. We aim to evaluate (1) how good LLMs are by themselves in generating…

人工智能 · 计算机科学 2023-02-15 Karthik Valmeekam , Sarath Sreedharan , Matthew Marquez , Alberto Olmo , Subbarao Kambhampati

Science journalism reports current scientific discoveries to non-specialists, aiming to enable public comprehension of the state of the art. However, this task can be challenging as the audience often lacks specific knowledge about the…

计算与语言 · 计算机科学 2024-07-16 Gongyao Jiang , Xinran Shi , Qiong Luo

Writing competitive programming problems is exacting. Authors must: set constraints, input distributions, and edge cases that rule out shortcuts; target specific algorithms (e.g., max-flow, dynamic programming, data structures); and…

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

Large language models (LLMs) have achieved remarkable progress across domains and applications but face challenges such as high fine-tuning costs, inference latency, limited edge deployability, and reliability concerns. Small language…

计算与语言 · 计算机科学 2025-11-06 Fali Wang , Jihai Chen , Shuhua Yang , Ali Al-Lawati , Linli Tang , Hui Liu , Suhang Wang

The ability of large language models (LLMs) to engage in credible dialogues with humans, taking into account the training data and the context of the conversation, has raised discussions about their ability to exhibit intrinsic motivations,…

人工智能 · 计算机科学 2023-11-16 Arlindo L. Oliveira , Tiago Domingos , Mário Figueiredo , Pedro U. Lima

Large Language Models (LLMs) like GPT-4 have revolutionized natural language processing, showing remarkable linguistic proficiency and reasoning capabilities. However, their application in strategic multi-agent decision-making environments…

计算与语言 · 计算机科学 2024-05-29 Chuanhao Li , Runhan Yang , Tiankai Li , Milad Bafarassat , Kourosh Sharifi , Dirk Bergemann , Zhuoran Yang

Using large language models (LLMs) for automatic evaluation has become an important evaluation method in NLP research. However, it is unclear whether these LLM-based evaluators can be applied in real-world classrooms to assess student…

计算与语言 · 计算机科学 2024-09-24 Cheng-Han Chiang , Wei-Chih Chen , Chun-Yi Kuan , Chienchou Yang , Hung-yi Lee

Large Language Models (LLMs) have demonstrated impressive capabilities in creative tasks such as storytelling and E-mail generation. However, as LLMs are primarily trained on final text results rather than intermediate revisions, it might…

计算与语言 · 计算机科学 2023-12-21 Lei Shu , Liangchen Luo , Jayakumar Hoskere , Yun Zhu , Yinxiao Liu , Simon Tong , Jindong Chen , Lei Meng

The advent of Large Language Models (LLM) has revolutionized the efficiency and speed with which tasks are completed, marking a significant leap in productivity through technological innovation. As these chatbots tackle increasingly complex…

软件工程 · 计算机科学 2024-05-24 Luc Bryan Heitz , Joun Chamas , Christopher Scherb

Large language models (LLMs) have increased the demand for personalized and stylish content generation. However, closed-source models like GPT-4 present limitations in optimization opportunities, while the substantial training costs and…

计算与语言 · 计算机科学 2024-10-07 Chenning Xu , Fangxun Shu , Dian Jin , Jinghao Wei , Hao Jiang

With LLMs shifting their role from statistical modeling of language to serving as general-purpose AI agents, how should LLM evaluations change? Arguably, a key ability of an AI agent is to flexibly combine, as needed, the basic skills it…

计算与语言 · 计算机科学 2023-10-27 Dingli Yu , Simran Kaur , Arushi Gupta , Jonah Brown-Cohen , Anirudh Goyal , Sanjeev Arora

The pursuit of human-level artificial intelligence (AI) has significantly advanced the development of autonomous agents and Large Language Models (LLMs). LLMs are now widely utilized as decision-making agents for their ability to interpret…

This study examines how four prominent large language models (Claude 3.7 Sonnet, GPT-4o, Gemini 2.5 Flash, and Deepseek-V3) handle sexually oriented requests through qualitative content analysis. By evaluating responses to prompts ranging…

计算机与社会 · 计算机科学 2026-02-10 Huiqian Lai

Large Language Models (LLMs) based autonomous agents demonstrate multifaceted capabilities to contribute substantially to economic production. However, existing benchmarks remain focused on single agentic capability, failing to capture…

The use of language models for automatically evaluating long-form text (LLM-as-a-judge) is becoming increasingly common, yet most LLM judges are optimized exclusively for English, with strategies for enhancing their multilingual evaluation…

Evaluating the writing capabilities of large language models (LLMs) remains a significant challenge due to the multidimensional nature of writing skills and the limitations of existing metrics. LLM's performance in thousand-words level and…

计算与语言 · 计算机科学 2026-04-22 Andrew Zhuoer Feng , Cunxiang Wang , Yu Luo , Lin Fan , Yilin Zhou , Zikang Wang , Xiaotao Gu , Jie Tang , Hongning Wang , Minlie Huang

The rapid evolution of Large Language Models (LLMs) has made them powerful tools for enhancing student writing. This study explores the extent and limitations of LLMs in assisting secondary-level English as a Foreign Language (EFL) students…

人机交互 · 计算机科学 2026-04-20 Hengky Susanto , David James Woo , Chingyi Yeung , Stephanie Wing Yan Lo-Philip , Chi Ho Yeung

The recent swift development of LLMs like GPT-4, Gemini, and GPT-3.5 offers a transformative opportunity in medicine and healthcare, especially in digital diagnostics. This study evaluates each model diagnostic abilities by interpreting a…

计算与语言 · 计算机科学 2024-05-14 Gaurav Kumar Gupta , Aditi Singh , Sijo Valayakkad Manikandan , Abul Ehtesham

Recent advances on large language models (LLMs) enable researchers and developers to build autonomous language agents that can automatically solve various tasks and interact with environments, humans, and other agents using natural language…