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Large Language Models (LLMs) possess substantial reasoning capabilities and are increasingly applied to optimization tasks, particularly in synergy with evolutionary computation. However, while recent surveys have explored specific aspects…

神经与进化计算 · 计算机科学 2026-01-08 Yisong Zhang , Ran Cheng , Guoxing Yi , Kay Chen Tan

Large language models and autonomous AI agents have evolved rapidly, resulting in a diverse array of evaluation benchmarks, frameworks, and collaboration protocols. Driven by the growing need for standardized evaluation and integration, we…

人工智能 · 计算机科学 2026-03-10 Mohamed Amine Ferrag , Norbert Tihanyi , Merouane Debbah

The explosive growth of Large Language Models (LLMs), such as GPT-4 with 1.8 trillion parameters, demands a fundamental rethinking of data center architecture to ensure scalability, efficiency, and cost-effectiveness. Our work provides a…

硬件体系结构 · 计算机科学 2025-09-09 Jesmin Jahan Tithi , Hanjiang Wu , Avishaii Abuhatzera , Fabrizio Petrini

Artificial Intelligence is moving from models that only generate text to Agentic AI, where systems behave as autonomous entities that can perceive, reason, plan, and act. Large Language Models (LLMs) are no longer used only as passive…

人工智能 · 计算机科学 2026-01-21 Arunkumar V , Gangadharan G. R. , Rajkumar Buyya

Recent breakthroughs in generative reasoning have fundamentally reshaped how large language models (LLMs) address complex tasks, enabling them to dynamically retrieve, refine, and organize information into coherent multi-step reasoning…

机器学习 · 计算机科学 2026-01-06 Mohamed Amine Ferrag , Norbert Tihanyi , Merouane Debbah

The evolution of Large Language Models (LLMs) from passive text generators to autonomous, goal-driven systems represents a fundamental shift in artificial intelligence. This chapter examines the emergence of agentic AI systems that…

人工智能 · 计算机科学 2026-01-07 Nadia Sibai , Yara Ahmed , Serry Sibaee , Sawsan AlHalawani , Adel Ammar , Wadii Boulila

The rapid progress of Multimodal Large Language Models(MLLMs) has transformed the AI landscape. These models combine pre-trained LLMs with various modality encoders. This integration requires a systematic understanding of how different…

计算与语言 · 计算机科学 2025-06-06 Jisu An , Junseok Lee , Jeoungeun Lee , Yongseok Son

The era of intelligent agents is upon us, driven by revolutionary advancements in large language models. Large Language Model (LLM) agents, with goal-driven behaviors and dynamic adaptation capabilities, potentially represent a critical…

The burgeoning field of Large Language Models (LLMs), exemplified by sophisticated models like OpenAI's ChatGPT, represents a significant advancement in artificial intelligence. These models, however, bring forth substantial challenges in…

The paradigm of Large Language Models (LLMs) is currently defined by auto-regressive (AR) architectures, which generate text through a sequential ``brick-by-brick'' process. Despite their success, AR models are inherently constrained by a…

Large Language Models (LLMs) like GPT and LLaMA are revolutionizing the AI industry with their sophisticated capabilities. Training these models requires vast GPU clusters and significant computing time, posing major challenges in terms of…

Large language model (LLM) agents increasingly operate in settings where a single context window is far too small to capture what has happened, what was learned, and what should not be repeated. Memory -- the ability to persist, organize,…

人工智能 · 计算机科学 2026-03-10 Pengfei Du

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…

Artificial intelligence (AI) has achieved human-level performance in specialized tasks such as Go, image recognition, and protein folding, raising the prospect of an AI singularity-where machines not only match but surpass human reasoning.…

流体动力学 · 物理学 2025-12-30 Zhongxin Yang , Yuanwei Bin , Yipeng Shi , Xiang I. A. Yang

The period from 2019 to the present marks one of the most significant paradigm shifts in information retrieval (IR) and natural language processing (NLP), culminating in the emergence of powerful large language models (LLMs) from 2022…

信息检索 · 计算机科学 2026-03-17 Zhichao Xu , Fengran Mo , Zhiqi Huang , Crystina Zhang , Puxuan Yu , Bei Wang , Jimmy Lin , Vivek Srikumar

Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language. As a major approach,…

Large Language Models (LLMs) have delivered impressive results in language understanding, generation, reasoning, and pushes the ability boundary of multimodal models. Transformer models, as the foundation of modern LLMs, offer a strong…

Large language models (LLMs) have revolutionized the field of artificial intelligence, endowing it with sophisticated language understanding and generation capabilities. However, when faced with more complex and interconnected tasks that…

人工智能 · 计算机科学 2023-10-06 Thorsten Händler

The rapid evolution of artificial intelligence (AI), especially in the domain of Large Language Models (LLMs) and generative AI, has opened new avenues for application across various fields, yet its role in business education remains…

计算与语言 · 计算机科学 2024-01-09 Vahid Ashrafimoghari , Necdet Gürkan , Jordan W. Suchow

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
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