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Large-scale language models (LLMs) have emerged as a groundbreaking innovation in the realm of question-answering and conversational agents. These models, leveraging different deep learning architectures such as Transformers, are trained on…

软件工程 · 计算机科学 2023-07-18 Fardin Ahsan Sakib , Saadat Hasan Khan , A. H. M. Rezaul Karim

Recent advancements in code large language models (LLMs) have demonstrated remarkable capabilities in code generation and understanding. It is still challenging to build a code LLM with comprehensive performance yet ultimate efficiency.…

Recent breakthroughs in large language models (LLMs) have centered around a handful of data-rich languages. What does it take to broaden access to breakthroughs beyond first-class citizen languages? Our work introduces Aya, a massively…

Many recent papers have studied the development of superforecaster-level event forecasting LLMs. While methodological problems with early studies cast doubt on the use of LLMs for event forecasting, recent studies with improved evaluation…

机器学习 · 计算机科学 2025-07-28 Sang-Woo Lee , Sohee Yang , Donghyun Kwak , Noah Y. Siegel

We introduce xLLM, an intelligent and efficient Large Language Model (LLM) inference framework designed for high-performance, large-scale enterprise-grade serving, with deep optimizations for diverse AI accelerators. To address these…

This study investigates the design, development, and evaluation of a Large Language Model (LLM)-based chatbot for teaching English conversations in an English as a Foreign Language (EFL) context. Employing the Design and Development…

Large Language Models (LLMs) have achieved remarkable success across a wide range of tasks, but serving them efficiently at scale remains a critical challenge due to their substantial computational and latency demands. While most existing…

分布式、并行与集群计算 · 计算机科学 2026-03-04 Yifan Sun , Gholamreza Haffari , Minxian Xu , Rajkumar Buyya , Adel N. Toosi

While training large language models (LLMs) from scratch can indeed lead to models with distinct capabilities and strengths, it incurs substantial costs and may lead to redundancy in competencies. Knowledge fusion aims to integrate existing…

计算与语言 · 计算机科学 2024-08-16 Fanqi Wan , Longguang Zhong , Ziyi Yang , Ruijun Chen , Xiaojun Quan

The advent of large language models (LLMs), such as GPT, Gemini, and DeepSeek, has significantly advanced natural language processing, giving rise to sophisticated chatbots capable of diverse language-related tasks. The transition from…

Large Language Models (LLMs) have made significant progress in recent years, achieving remarkable results in question-answering tasks (QA). However, they still face two major challenges: hallucination and outdated information after the…

Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of general-domain tasks. However, their effectiveness in specialized fields, such as construction, remains underexplored. In this paper, we introduce…

计算与语言 · 计算机科学 2025-08-25 Yanzhao Wu , Lufan Wang , Rui Liu

Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling natural language processing tasks that were previously thought to be exclusive to humans. In this work, we introduce Qwen, the first installment…

In the rapidly evolving landscape of cyber security, intelligent chatbots are gaining prominence. Artificial Intelligence, Machine Learning, and Natural Language Processing empower these chatbots to handle user inquiries and deliver threat…

Large Language Models (LLMs) drive scientific question-answering on modern search engines, yet their evaluation robustness remains underexplored. We introduce YESciEval, an open-source framework that combines fine-grained rubric-based…

计算与语言 · 计算机科学 2025-05-30 Jennifer D'Souza , Hamed Babaei Giglou , Quentin Münch

In the rapidly evolving field of artificial intelligence, large language models (LLMs) have demonstrated significant capabilities across numerous applications. However, the performance of these models in languages with fewer resources, such…

计算与语言 · 计算机科学 2024-05-24 Birger Moell

With the profound development of large language models(LLMs), their safety concerns have garnered increasing attention. However, there is a scarcity of Chinese safety benchmarks for LLMs, and the existing safety taxonomies are inadequate,…

计算与语言 · 计算机科学 2024-09-04 Wenjing Zhang , Xuejiao Lei , Zhaoxiang Liu , Meijuan An , Bikun Yang , KaiKai Zhao , Kai Wang , Shiguo Lian

The rapid adoption of Mixture-of-Experts (MoE) architectures marks a major shift in the deployment of Large Language Models (LLMs). MoE LLMs improve scaling efficiency by activating only a small subset of parameters per token, but their…

密码学与安全 · 计算机科学 2026-02-10 Jona te Lintelo , Lichao Wu , Stjepan Picek

The advance of Artificial Intelligence (AI) is continuously reshaping the future 6G wireless communications. Particularly, the development of Large Language Models (LLMs) offers a promising approach to effectively improve the performance…

信息论 · 计算机科学 2025-03-10 Tianyue Zheng , Linglong Dai

Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource languages. To mitigate this challenge, we present FuxiTranyu,…

Large Language Models (LLMs) are key technologies driving intelligent systems to handle multiple tasks. To meet the demands of various tasks, an increasing number of LLMs-driven experts with diverse capabilities have been developed,…

人工智能 · 计算机科学 2024-12-06 Yuanshuai Wang , Xingjian Zhang , Jinkun Zhao , Siwei Wen , Peilin Feng , Shuhao Liao , Lei Huang , Wenjun Wu