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相关论文: Large Language Models Meet Computer Vision: A Brie…

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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…

Artificial intelligence (AI) technology has advanced rapidly in recent years, with large language models (LLMs) emerging as a significant breakthrough. LLMs are increasingly making an impact across various industries, with the medical field…

人工智能 · 计算机科学 2025-09-24 Zhiyu Kan , Wensheng Gan , Zhenlian Qi , Philip S. Yu

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…

机器人学 · 计算机科学 2024-08-16 Yeseung Kim , Dohyun Kim , Jieun Choi , Jisang Park , Nayoung Oh , Daehyung Park

Reinforcement learning (RL) has shown impressive results in sequential decision-making tasks. Meanwhile, Large Language Models (LLMs) and Vision-Language Models (VLMs) have emerged, exhibiting impressive capabilities in multimodal…

The development of Large Vision-Language Models (LVLMs) is striving to catch up with the success of Large Language Models (LLMs), yet it faces more challenges to be resolved. Very recent works enable LVLMs to localize object-level visual…

计算机视觉与模式识别 · 计算机科学 2024-03-20 Zhipeng Huang , Zhizheng Zhang , Zheng-Jun Zha , Yan Lu , Baining Guo

In this survey, we address the key challenges in Large Language Models (LLM) research, focusing on the importance of interpretability. Driven by increasing interest from AI and business sectors, we highlight the need for transparency in…

计算与语言 · 计算机科学 2024-07-23 Erik Cambria , Lorenzo Malandri , Fabio Mercorio , Navid Nobani , Andrea Seveso

Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment. However, the…

Large language models (LLMs) have made significant advancements in natural language understanding. However, through that enormous semantic representation that the LLM has learnt, is it somehow possible for it to understand images as well?…

计算机视觉与模式识别 · 计算机科学 2024-07-12 Mu Cai , Zeyi Huang , Yuheng Li , Utkarsh Ojha , Haohan Wang , Yong Jae Lee

Large language models (LLMs) are powerful artificial intelligence (AI) tools transforming how research is conducted. However, their use in research has been met with skepticism, due to concerns about hallucinations, biases and potential…

人工智能 · 计算机科学 2025-07-08 Ruian Ke , Ruy M. Ribeiro

Machine Translation (MT) has greatly advanced over the years due to the developments in deep neural networks. However, the emergence of Large Language Models (LLMs) like GPT-4 and ChatGPT is introducing a new phase in the MT domain. In this…

计算与语言 · 计算机科学 2024-04-03 Chenyang Lyu , Zefeng Du , Jitao Xu , Yitao Duan , Minghao Wu , Teresa Lynn , Alham Fikri Aji , Derek F. Wong , Siyou Liu , Longyue Wang

The recent progression of Large Language Models (LLMs) has witnessed great success in the fields of data-centric applications. LLMs trained on massive textual datasets showed ability to encode not only context but also ability to provide…

密码学与安全 · 计算机科学 2024-05-24 Mohammed Hassanin , Nour Moustafa

The emergence of Generative Artificial Intelligence (AI) and Large Language Models (LLMs) has marked a new era of Natural Language Processing (NLP), introducing unprecedented capabilities that are revolutionizing various domains. This paper…

计算与语言 · 计算机科学 2024-08-26 Desta Haileselassie Hagos , Rick Battle , Danda B. Rawat

Large Language Models (LLMs) have seen significant use in domains such as natural language processing and computer vision. Going beyond text, image and graphics, LLMs present a significant potential for analysis of time series data,…

机器学习 · 计算机科学 2024-05-08 Xiyuan Zhang , Ranak Roy Chowdhury , Rajesh K. Gupta , Jingbo Shang

In the rapidly evolving landscape of genomics, deep learning has emerged as a useful tool for tackling complex computational challenges. This review focuses on the transformative role of Large Language Models (LLMs), which are mostly based…

With the emergence of Large Language Models (LLMs) and Vision Foundation Models (VFMs), multimodal AI systems benefiting from large models have the potential to equally perceive the real world, make decisions, and control tools as humans.…

Large Language Models (LLMs) have introduced a paradigm shift in interaction with AI technology, enabling knowledge workers to complete tasks by specifying their desired outcome in natural language. LLMs have the potential to increase…

人机交互 · 计算机科学 2025-03-24 Michelle Brachman , Amina El-Ashry , Casey Dugan , Werner Geyer

The fusion of language and vision in large vision-language models (LVLMs) has revolutionized deep learning-based object detection by enhancing adaptability, contextual reasoning, and generalization beyond traditional architectures. This…

计算机视觉与模式识别 · 计算机科学 2025-10-01 Ranjan Sapkota , Manoj Karkee

The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia and industry. To mitigate potential discrimination and…

Large Language Models (LLMs), AI-driven models that can achieve general-purpose language understanding and generation, have emerged as a transformative force, revolutionizing fields well beyond Natural Language Processing (NLP) and…

信息论 · 计算机科学 2024-02-27 Ali Maatouk , Nicola Piovesan , Fadhel Ayed , Antonio De Domenico , Merouane Debbah

In recent years, the rapid advancement of machine learning (ML) models, particularly transformer-based pre-trained models, has revolutionized Natural Language Processing (NLP) and Computer Vision (CV) fields. However, researchers have…

计算与语言 · 计算机科学 2023-09-27 Nayeon Lee , Yejin Bang , Holy Lovenia , Samuel Cahyawijaya , Wenliang Dai , Pascale Fung