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Related papers: MM-LLMs: Recent Advances in MultiModal Large Langu…

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Large language models (LLMs) are gaining increasing popularity in both academia and industry, owing to their unprecedented performance in various applications. As LLMs continue to play a vital role in both research and daily use, their…

Computation and Language · Computer Science 2024-01-01 Yupeng Chang , Xu Wang , Jindong Wang , Yuan Wu , Linyi Yang , Kaijie Zhu , Hao Chen , Xiaoyuan Yi , Cunxiang Wang , Yidong Wang , Wei Ye , Yue Zhang , Yi Chang , Philip S. Yu , Qiang Yang , Xing Xie

In recent years, the integration of large language models (LLMs) has revolutionized the field of robotics, enabling robots to communicate, understand, and reason with human-like proficiency. This paper explores the multifaceted impact of…

Robotics · Computer Science 2024-08-16 Yeseung Kim , Dohyun Kim , Jieun Choi , Jisang Park , Nayoung Oh , Daehyung Park

Recently, the astonishing performance of large language models (LLMs) in natural language comprehension and generation tasks triggered lots of exploration of using them as central controllers to build agent systems. Multiple studies focus…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Chenyu Wang , Weixin Luo , Sixun Dong , Xiaohua Xuan , Zhengxin Li , Lin Ma , Shenghua Gao

Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as text. LMs have a wide range of applications in natural language…

Large language models (LLMs) have shown impressive capabilities across a wide range of language tasks. However, their reasoning process is primarily guided by statistical patterns in training data, which limits their ability to handle novel…

Artificial Intelligence · Computer Science 2025-08-21 Hong Su

Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications. Despite the importance and recent progress, most existing works on personalized LLMs have focused either entirely…

Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence. The application of LLMs extends beyond conventional…

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

Large language models (LLMs) have demonstrated remarkable capabilities across various NLP tasks and have recently expanded their impact to coding tasks, bridging the gap between natural languages (NL) and programming languages (PL). This…

Computation and Language · Computer Science 2024-12-12 Nishat Raihan , Christian Newman , Marcos Zampieri

The advent of Large Language Models (LLMs) has brought in a new era of possibilities in the realm of education. This survey paper summarizes the various technologies of LLMs in educational settings from multifaceted perspectives,…

Computation and Language · Computer Science 2024-04-03 Shen Wang , Tianlong Xu , Hang Li , Chaoli Zhang , Joleen Liang , Jiliang Tang , Philip S. Yu , Qingsong Wen

Large language models (LLMs) have revolutionized natural language processing with their exceptional understanding, synthesizing, and reasoning capabilities. However, deploying LLMs on resource-constrained edge devices presents significant…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-02-25 Yue Zheng , Yuhao Chen , Bin Qian , Xiufang Shi , Yuanchao Shu , Jiming Chen

Large language models (LLMs) have demonstrated remarkable potential in handling multilingual machine translation (MMT). In this paper, we systematically investigate the advantages and challenges of LLMs for MMT by answering two questions:…

Computation and Language · Computer Science 2024-06-17 Wenhao Zhu , Hongyi Liu , Qingxiu Dong , Jingjing Xu , Shujian Huang , Lingpeng Kong , Jiajun Chen , Lei Li

Strong Artificial Intelligence (Strong AI) or Artificial General Intelligence (AGI) with abstract reasoning ability is the goal of next-generation AI. Recent advancements in Large Language Models (LLMs), along with the emerging field of…

Computation and Language · Computer Science 2024-01-19 Yiqi Wang , Wentao Chen , Xiaotian Han , Xudong Lin , Haiteng Zhao , Yongfei Liu , Bohan Zhai , Jianbo Yuan , Quanzeng You , Hongxia Yang

In recent years, large language models (LLMs) have achieved remarkable success in natural language processing (NLP). LLMs require an extreme amount of parameters to attain high performance. As models grow into the trillion-parameter range,…

Computation and Language · Computer Science 2024-09-10 Zhyar Rzgar K Rostam , Sándor Szénási , Gábor Kertész

We present MM1.5, a new family of multimodal large language models (MLLMs) designed to enhance capabilities in text-rich image understanding, visual referring and grounding, and multi-image reasoning. Building upon the MM1 architecture,…

Large language models (LLMs) and large multimodal models (LMMs) have achieved unprecedented breakthrough, showcasing remarkable capabilities in natural language understanding, generation, and complex reasoning. This transformative potential…

Machine Learning · Computer Science 2025-10-24 Hyun Jong Yang , Hyunsoo Kim , Hyeonho Noh , Seungnyun Kim , Byonghyo Shim

Large language models (LLMs) have demonstrated strong performance in general-purpose machine translation, but their effectiveness in complex, domain-sensitive translation tasks remains underexplored. Recent advancements in Large Reasoning…

Computation and Language · Computer Science 2025-05-27 Yongshi Ye , Biao Fu , Chongxuan Huang , Yidong Chen , Xiaodong Shi

Inspired by the exceptional general intelligence of Large Language Models (LLMs), researchers have begun to explore their application in pioneering the next generation of recommender systems - systems that are conversational, explainable,…

Information Retrieval · Computer Science 2024-08-06 Wensheng Lu , Jianxun Lian , Wei Zhang , Guanghua Li , Mingyang Zhou , Hao Liao , Xing Xie

Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS). These models, trained on massive…

Information Retrieval · Computer Science 2024-06-19 Likang Wu , Zhi Zheng , Zhaopeng Qiu , Hao Wang , Hongchao Gu , Tingjia Shen , Chuan Qin , Chen Zhu , Hengshu Zhu , Qi Liu , Hui Xiong , Enhong Chen

Large language models (LLMs) are increasingly being deployed across disciplines due to their advanced reasoning and problem solving capabilities. To measure their effectiveness, various benchmarks have been developed that measure aspects of…

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