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Large Language Models (LLMs) are becoming vital tools that help us solve and understand complex problems by acting as digital assistants. LLMs can generate convincing explanations, even when only given the inputs and outputs of these…

计算与语言 · 计算机科学 2024-10-14 Rohan Ajwani , Shashidhar Reddy Javaji , Frank Rudzicz , Zining Zhu

The recent success of Large Language Models (LLMs) has garnered significant attention in both academia and industry. Prior research on LLMs has primarily focused on enhancing or leveraging their generalization capabilities in zero- and…

计算与语言 · 计算机科学 2024-04-01 Shulin Liu , Chengcheng Xu , Hao Liu , Tinghao Yu , Tao Yang

Automated planning is concerned with developing efficient algorithms to generate plans or sequences of actions to achieve a specific goal in a given environment. Emerging Large Language Models (LLMs) can answer questions, write high-quality…

The advent of Large Language Models (LLMs) heralds a pivotal shift in online user interactions with information. Traditional Information Retrieval (IR) systems primarily relied on query-document matching, whereas LLMs excel in comprehending…

信息检索 · 计算机科学 2023-11-22 Samira Ghodratnama , Mehrdad Zakershahrak

Human reasoning involves different strategies, each suited to specific problems. Prior work shows that large language model (LLMs) tend to favor a single reasoning strategy, potentially limiting their effectiveness in diverse reasoning…

计算与语言 · 计算机科学 2025-07-17 Yanjian Zhang , Guillaume Wisniewski , Nadi Tomeh , Thierry Charnois

Large language models (LLMs) have recently been used as backbones for recommender systems. However, their performance often lags behind conventional methods in standard tasks like retrieval. We attribute this to a mismatch between LLMs'…

The development of large language models (LLMs) capable of following instructions and engaging in conversational interactions sparked increased interest in their utilization across various support tools. We investigate the utility of modern…

人机交互 · 计算机科学 2024-01-31 Tuhin Chakrabarty , Vishakh Padmakumar , Faeze Brahman , Smaranda Muresan

Fine-tuning Large Language Models (LLMs) incurs considerable training costs, driving the need for data-efficient training with optimised data ordering. Human-inspired strategies offer a solution by organising data based on human learning…

计算与语言 · 计算机科学 2024-11-06 Yushi Yang , Andrew M. Bean , Robert McCraith , Adam Mahdi

This paper explores the evolving relationship between clinician trust in LLMs, the transformation of data sources from predominantly human-generated to AI-generated content, and the subsequent impact on the precision of LLMs and clinician…

计算机与社会 · 计算机科学 2024-04-02 Avishek Choudhury , Zaria Chaudhry

Large Language Models (LLMs) are increasingly being integrated into software development processes, with the potential to transform team workflows and productivity. This paper investigates how LLMs affect team collaboration throughout the…

软件工程 · 计算机科学 2025-10-13 Devang Dhanuka

Large Language Models have been demonstrating broadly satisfactory generative abilities for users, which seems to be due to the intensive use of human feedback that refines responses. Nevertheless, suggestibility inherited via human…

计算与语言 · 计算机科学 2025-06-26 Leonardo Ranaldi , Giulia Pucci

Large language models (LLMs) have become common decision-support tools across educational and professional contexts, raising questions about how their outputs shape human critical thinking. Prior work suggests that the amount of AI…

Utilizing user profiles to personalize Large Language Models (LLMs) has been shown to enhance the performance on a wide range of tasks. However, the precise role of user profiles and their effect mechanism on LLMs remains unclear. This…

计算与语言 · 计算机科学 2024-06-27 Bin Wu , Zhengyan Shi , Hossein A. Rahmani , Varsha Ramineni , Emine Yilmaz

In recent years, Large Language Models (LLMs) have gained immense attention due to their notable emergent capabilities, surpassing those seen in earlier language models. A particularly intriguing application of LLMs is their role as…

计算与语言 · 计算机科学 2023-11-02 Xue-Yong Fu , Md Tahmid Rahman Laskar , Cheng Chen , Shashi Bhushan TN

Recently, Large Language Models (LLMs) have drawn significant attention due to their outstanding reasoning capabilities and extensive knowledge repository, positioning them as superior in handling various natural language processing tasks…

计算与语言 · 计算机科学 2023-11-30 Han Cao , Lingwei Wei , Mengyang Chen , Wei Zhou , Songlin Hu

Large Language Models (LLMs) represent a major step toward artificial general intelligence, significantly advancing our ability to interact with technology. While LLMs perform well on Natural Language Processing tasks -- such as…

计算与语言 · 计算机科学 2025-05-15 Brandon Smith , Mohamed Reda Bouadjenek , Tahsin Alamgir Kheya , Phillip Dawson , Sunil Aryal

The rapid advancement of artificial intelligence, particularly with the development of Large Language Models (LLMs) built on the transformer architecture, has redefined the capabilities of natural language processing. These models now…

计算与语言 · 计算机科学 2025-02-11 Andrea Matarazzo , Riccardo Torlone

Large Language Models (LLMs) were used to assist four Commonwealth Scientific and Industrial Research Organisation (CSIRO) researchers to perform systematic literature reviews (SLR). We evaluate the performance of LLMs for SLR tasks in…

计算与语言 · 计算机科学 2025-03-24 Lachlan McGinness , Peter Baumgartner

Intelligent systems must maintain and manipulate task-relevant information online to adapt to dynamic environments and changing goals. This capacity, known as working memory, is fundamental to human reasoning and intelligence. Despite…

机器学习 · 计算机科学 2026-04-14 Hua-Dong Xiong , Li Ji-An , Jiaqi Huang , Robert C. Wilson , Kwonjoon Lee , Xue-Xin Wei

Large Language Models (LLMs) are known to overuse certain terms like "delve" and "intricate." The exact reasons for these lexical choices, however, have been unclear. Using Meta's Llama model, this study investigates the contribution of…

计算与语言 · 计算机科学 2025-08-05 Tom S. Juzek , Zina B. Ward
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