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Large language models (LLMs) exhibit superior performance on various natural language tasks, but they are susceptible to issues stemming from outdated data and domain-specific limitations. In order to address these challenges, researchers…

Computation and Language · Computer Science 2024-10-24 Zhangyin Feng , Weitao Ma , Weijiang Yu , Lei Huang , Haotian Wang , Qianglong Chen , Weihua Peng , Xiaocheng Feng , Bing Qin , Ting liu

There have been rapid advancements in the capabilities of large language models (LLMs) in recent years, greatly revolutionizing the field of natural language processing (NLP) and artificial intelligence (AI) to understand and interact with…

Computation and Language · Computer Science 2024-09-26 Zeyneb N. Kaya , Souvick Ghosh

The reasoning capability of large language models (LLMs), defined as their ability to analyze, infer, and make decisions based on input information, is essential for building intelligent task-oriented dialogue systems. However, existing…

Computation and Language · Computer Science 2026-03-02 Yu Zhu , Kai Yang

Multi-agent large language models (MA-LLMs) are a rapidly growing research area that leverages multiple interacting language agents to tackle complex tasks, outperforming single-agent large language models. This literature review…

Multiagent Systems · Computer Science 2025-06-03 Arne Tillmann

Connecting text and visual modalities plays an essential role in generative intelligence. For this reason, inspired by the success of large language models, significant research efforts are being devoted to the development of Multimodal…

Computer Vision and Pattern Recognition · Computer Science 2024-06-07 Davide Caffagni , Federico Cocchi , Luca Barsellotti , Nicholas Moratelli , Sara Sarto , Lorenzo Baraldi , Lorenzo Baraldi , Marcella Cornia , Rita Cucchiara

User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary medium of human communication, forms the foundation of social interaction and behavior.…

We introduce a dynamic benchmarking system for conversational agents that evaluates their performance through a single, simulated, and lengthy user$\leftrightarrow$agent interaction. The interaction is a conversation between the user and…

Computation and Language · Computer Science 2024-10-14 David Castillo-Bolado , Joseph Davidson , Finlay Gray , Marek Rosa

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…

Computation and Language · Computer Science 2024-12-03 Jing Yi Wang , Nicholas Sukiennik , Tong Li , Weikang Su , Qianyue Hao , Jingbo Xu , Zihan Huang , Fengli Xu , Yong Li

With extensive pre-trained knowledge and high-level general capabilities, large language models (LLMs) emerge as a promising avenue to augment reinforcement learning (RL) in aspects such as multi-task learning, sample efficiency, and…

Machine Learning · Computer Science 2024-11-21 Yuji Cao , Huan Zhao , Yuheng Cheng , Ting Shu , Yue Chen , Guolong Liu , Gaoqi Liang , Junhua Zhao , Jinyue Yan , Yun Li

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…

Humans often interact with large language models (LLMs) in multi-turn interaction to obtain desired answers or more information. However, most existing studies overlook the multi-turn instruction following ability of LLMs, in terms of…

Computation and Language · Computer Science 2024-05-24 Yuchong Sun , Che Liu , Kun Zhou , Jinwen Huang , Ruihua Song , Wayne Xin Zhao , Fuzheng Zhang , Di Zhang , Kun Gai

Large Language Models (LLMs) have demonstrated wide-ranging applications across various fields and have shown significant potential in the academic peer-review process. However, existing applications are primarily limited to static review…

Computation and Language · Computer Science 2024-06-11 Cheng Tan , Dongxin Lyu , Siyuan Li , Zhangyang Gao , Jingxuan Wei , Siqi Ma , Zicheng Liu , Stan Z. Li

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across linguistic boundaries, but also represent an important…

Computation and Language · Computer Science 2024-11-20 Shaolin Zhu , Supryadi , Shaoyang Xu , Haoran Sun , Leiyu Pan , Menglong Cui , Jiangcun Du , Renren Jin , António Branco , Deyi Xiong

As large language models (LLMs) increasingly permeate daily lives, there is a growing demand for real-time interactions that mirror human conversations. Traditional turn-based chat systems driven by LLMs prevent users from verbally…

Computation and Language · Computer Science 2026-01-14 Xinrong Zhang , Yingfa Chen , Shengding Hu , Xu Han , Zihang Xu , Yuanwei Xu , Weilin Zhao , Maosong Sun , Zhiyuan Liu

The growing use of large language model (LLM)-based chatbots has raised concerns about fairness. Fairness issues in LLMs can lead to severe consequences, such as bias amplification, discrimination, and harm to marginalized communities.…

Computation and Language · Computer Science 2025-06-11 Zhiting Fan , Ruizhe Chen , Tianxiang Hu , Zuozhu Liu

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…

Neural and Evolutionary Computing · Computer Science 2026-01-08 Yisong Zhang , Ran Cheng , Guoxing Yi , Kay Chen Tan

The rapid advancement of Large Language Models (LLMs) has opened new possibilities in Multi-Robot Systems (MRS), enabling enhanced communication, task allocation and planning, and human-robot interaction. Unlike traditional single-robot and…

Robotics · Computer Science 2026-05-05 Peihan Li , Zijian An , Shams Abrar , Lifeng Zhou

The rise of Multimodal Large Language Models (MLLMs) has become a transformative force in the field of artificial intelligence, enabling machines to process and generate content across multiple modalities, such as text, images, audio, and…

Computation and Language · Computer Science 2025-12-09 Ming Li , Keyu Chen , Ziqian Bi , Ming Liu , Xinyuan Song , Zekun Jiang , Tianyang Wang , Benji Peng , Qian Niu , Junyu Liu , Jinlang Wang , Sen Zhang , Xuanhe Pan , Jiawei Xu , Pohsun Feng

Large language model-based multi-agent systems have recently gained significant attention due to their potential for complex, collaborative, and intelligent problem-solving capabilities. Existing surveys typically categorize LLM-based…

Multiagent Systems · Computer Science 2026-05-27 Bingyu Yan , Zhibo Zhou , Litian Zhang , Lian Zhang , Ziyi Zhou , Dezhuang Miao , Zhoujun Li , Chaozhuo Li , Xiaoming Zhang

Large Language Models (LLMs) have become a popular interface for human-AI interaction, supporting information seeking and task assistance through natural, multi-turn dialogue. To respond to users within multi-turn dialogues, the…

Computation and Language · Computer Science 2026-04-16 Fengran Mo , Yifan Gao , Sha Li , Hansi Zeng , Xin Liu , Zhaoxuan Tan , Xian Li , Jianshu Chen , Dakuo Wang , Meng Jiang