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Large language models (LLMs) have greatly impacted the natural language processing (NLP) field, particularly for the English language. These models have demonstrated capabilities in understanding and generating human-like text. The success…

计算与语言 · 计算机科学 2024-07-10 Hasna Chouikhi , Manel Aloui , Cyrine Ben Hammou , Ghaith Chaabane , Haithem Kchaou , Chehir Dhaouadi

Large Language Models (LLMs) have demonstrated remarkable potential in diverse domains, yet their application in the legal sector, particularly in low-resource contexts, remains limited. This study addresses the challenges of adapting LLMs…

计算与语言 · 计算机科学 2024-12-20 Rabee Qasem , Mohannad Hendi , Banan Tantour

In the rapidly evolving landscape of artificial intelligence (AI), generative large language models (LLMs) stand at the forefront, revolutionizing how we interact with our data. However, the computational intensity and memory consumption of…

机器学习 · 计算机科学 2025-07-24 Xupeng Miao , Gabriele Oliaro , Zhihao Zhang , Xinhao Cheng , Hongyi Jin , Tianqi Chen , Zhihao Jia

Large Language Models (LLMs) are playing an increasingly important role in physics research by assisting with symbolic manipulation, numerical computation, and scientific reasoning. However, ensuring the reliability, transparency, and…

人工智能 · 计算机科学 2025-08-19 Yinggan Xu , Hana Kimlee , Yijia Xiao , Di Luo

Language is far more than a communication tool. A wealth of information - including but not limited to the identities, psychological states, and social contexts of its users - can be gleaned through linguistic markers, and such insights are…

Large Language Models (LLMs) excel at producing broadly relevant text, but this generality becomes a limitation when user-specific preferences are required, such as recommending restaurants or planning travel. In these scenarios, users…

Large Language Models (LLMs) have revolutionized various fields with their exceptional capabilities in understanding, processing, and generating human-like text. This paper investigates the potential of LLMs in advancing Network Intrusion…

密码学与安全 · 计算机科学 2025-07-08 Shuo Yang , Xinran Zheng , Xinchen Zhang , Jinfeng Xu , Jinze Li , Donglin Xie , Weicai Long , Edith C. H. Ngai

Large Language Models (LLMs) have made significant progress in advancing artificial general intelligence (AGI), leading to the development of increasingly large models such as GPT-4 and LLaMA-405B. However, scaling up model sizes results in…

计算与语言 · 计算机科学 2026-02-23 Lihu Chen , Gaël Varoquaux

Are AI systems truly representing human values, or merely averaging across them? Our study suggests a concerning reality: Large Language Models (LLMs) fail to represent diverse cultural moral frameworks despite their linguistic…

计算与语言 · 计算机科学 2025-08-01 Simon Münker

Large language models (LLM) are advanced AI systems trained on extensive textual data, leveraging deep learning techniques to understand and generate human-like language. Today's LLMs with billions of parameters are so huge that hardly any…

分布式、并行与集群计算 · 计算机科学 2025-10-14 Sheikh Azizul Hakim , Saem Hasan

The rapid evolution of large language models (LLMs) and their capacity to simulate human cognition and behavior has given rise to LLM-based frameworks and tools that are evaluated and applied based on their ability to perform tasks…

计算与语言 · 计算机科学 2024-12-03 Jing Yi Wang , Nicholas Sukiennik , Tong Li , Weikang Su , Qianyue Hao , Jingbo Xu , Zihan Huang , Fengli Xu , Yong Li

Large language models (LLMs) have been widely deployed in various applications, often functioning as autonomous agents that interact with each other in multi-agent systems. While these systems have shown promise in enhancing capabilities…

人工智能 · 计算机科学 2025-12-05 Jae Hee Lee , Anne Lauscher , Stefano V. Albrecht

Large language models (LLMs) have gained popularity recently due to their outstanding performance in various downstream Natural Language Processing (NLP) tasks. However, low-resource languages are still lagging behind current…

Large language models (LLMs) are increasingly proposed for crisis preparedness and response, particularly for multilingual communication. However, their suitability for high-stakes crisis contexts remains insufficiently evaluated. This work…

计算与语言 · 计算机科学 2026-02-17 Belu Ticona , Antonis Anastasopoulos

Autonomous vehicles (AVs) rely on sophisticated perception systems to interpret their surroundings, a cornerstone for safe navigation and decision-making. The integration of Large Language Models (LLMs) into AV perception frameworks offers…

机器人学 · 计算机科学 2024-12-31 Athanasios Karagounis

Modern Large Language Models (LLMs) exhibit impressive zero-shot and few-shot generalization capabilities across complex natural language tasks, enabling their widespread use as virtual assistants for diverse applications such as…

计算与语言 · 计算机科学 2025-06-19 Arjun Vaithilingam Sudhakar

Large Language Models (LLMs) offer transformative potential for Modeling & Simulation (M&S) through natural language interfaces that simplify workflows. However, over-reliance risks compromising quality due to ambiguities, logical…

软件工程 · 计算机科学 2025-06-16 Philippe J. Giabbanelli , John Beverley , Istvan David , Andreas Tolk

Optimization algorithms and large language models (LLMs) enhance decision-making in dynamic environments by integrating artificial intelligence with traditional techniques. LLMs, with extensive domain knowledge, facilitate intelligent…

神经与进化计算 · 计算机科学 2024-05-17 Sen Huang , Kaixiang Yang , Sheng Qi , Rui Wang

Pretrained language models (PLMs) have produced substantial improvements in discourse-aware neural machine translation (NMT), for example, improved coherence in spoken language translation. However, the underlying reasons for their strong…

计算与语言 · 计算机科学 2023-06-01 Zhihong Huang , Longyue Wang , Siyou Liu , Derek F. Wong

Large Language Models (LLMs) represent a leap in artificial intelligence, excelling in tasks using human language(s). Although the main focus of general-purpose LLMs is not code generation, they have shown promising results in the domain.…

软件工程 · 计算机科学 2024-01-30 Sanka Rasnayaka , Guanlin Wang , Ridwan Shariffdeen , Ganesh Neelakanta Iyer