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Large Language Models (LLMs) are transforming artificial intelligence, enabling autonomous agents to perform diverse tasks across various domains. These agents, proficient in human-like text comprehension and generation, have the potential…

Artificial Intelligence · Computer Science 2024-04-10 Saikat Barua

Large Language Models (LLMs), with remarkable conversational capability, have emerged as AI assistants that can handle both visual and textual modalities. However, their effectiveness in joint video and language understanding has not been…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ruipu Luo , Ziwang Zhao , Min Yang , Zheming Yang , Minghui Qiu , Tao Wang , Zhongyu Wei , Yanhao Wang , Cen Chen

Although recent end-to-end video generation models demonstrate impressive performance in visually oriented content creation, they remain limited in scenarios that require strict logical rigor and precise knowledge representation, such as…

Artificial Intelligence · Computer Science 2026-02-13 Lingyong Yan , Jiulong Wu , Dong Xie , Weixian Shi , Deguo Xia , Jizhou Huang

The rapid advancement of Large Language Models (LLMs) has marked a significant breakthrough in Artificial Intelligence (AI), ushering in a new era of Human-centered Artificial Intelligence (HAI). HAI aims to better serve human welfare and…

Robotics · Computer Science 2025-10-29 Wenbin Ding , Jun Chen , Mingjia Chen , Fei Xie , Qi Mao , Philip Dames

The emergence of Large Language Models (LLMs) has reshaped agent systems. Unlike traditional rule-based agents with limited task scope, LLM-powered agents offer greater flexibility, cross-domain reasoning, and natural language interaction.…

Artificial Intelligence · Computer Science 2026-05-05 Guannan Liang , Qianqian Tong

The recent advance in Large Language Models (LLMs) has shaped a new paradigm of AI agents, i.e., LLM-based agents. Compared to standalone LLMs, LLM-based agents substantially extend the versatility and expertise of LLMs by enhancing LLMs…

Software Engineering · Computer Science 2025-12-04 Junwei Liu , Kaixin Wang , Yixuan Chen , Xin Peng , Zhenpeng Chen , Lingming Zhang , Yiling Lou

The rapid advancement of large language models (LLMs) and multimodal learning has transformed digital content creation and manipulation. Traditional visual editing tools require significant expertise, limiting accessibility. Recent strides…

Computer Vision and Pattern Recognition · Computer Science 2024-11-22 Thanh Tam Nguyen , Zhao Ren , Trinh Pham , Thanh Trung Huynh , Phi Le Nguyen , Hongzhi Yin , Quoc Viet Hung Nguyen

Large Language Model (LLM) agents are transforming education by automating complex pedagogical tasks and enhancing both teaching and learning processes. In this survey, we present a systematic review of recent advances in applying LLM…

Computers and Society · Computer Science 2026-02-05 Zhendong Chu , Shen Wang , Jian Xie , Tinghui Zhu , Yibo Yan , Jinheng Ye , Aoxiao Zhong , Xuming Hu , Jing Liang , Philip S. Yu , Qingsong Wen

Recent advancements in Large Language Models (LLMs) have shown significant progress in understanding complex natural language. One important application of LLM is LLM-based AI Agent, which leverages the ability of LLM as well as external…

Computation and Language · Computer Science 2024-07-19 Zelong Li , Shuyuan Xu , Kai Mei , Wenyue Hua , Balaji Rama , Om Raheja , Hao Wang , He Zhu , Yongfeng Zhang

Simulations, although powerful in accurately replicating real-world systems, often remain inaccessible to non-technical users due to their complexity. Conversely, large language models (LLMs) provide intuitive, language-based interactions…

Computation and Language · Computer Science 2025-05-22 Jacob Kleiman , Kevin Frank , Joseph Voyles , Sindy Campagna

Since ancient times, mechanical design aids have been developed to assist human users, aimed at improving the efficiency and effectiveness of design. However, even with the widespread use of contemporary Computer-Aided Design (CAD) systems,…

Computational Engineering, Finance, and Science · Computer Science 2024-08-06 Jiaxing Lu , Heran Li , Fangwei Ning , Yixuan Wang , Xinze Li , Yan Shi

While Vision-language models (VLMs) have demonstrated remarkable performance across multi-modal tasks, their choice of vision encoders presents a fundamental weakness: their low-level features lack the robust structural and spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-01-01 Brandon Huang , Hang Hua , Zhuoran Yu , Trevor Darrell , Rogerio Feris , Roei Herzig

Modern-day Integrated Development Environments (IDEs) have come a long way from the early text editing utilities to the complex programs encompassing thousands of functions to help developers. However, with the increasing number of…

Software Engineering · Computer Science 2024-02-20 Yaroslav Zharov , Yury Khudyakov , Evgeniia Fedotova , Evgeny Grigorenko , Egor Bogomolov

Video content remains largely inaccessible to blind and low-vision (BLV) users. To address this, we introduce a prototype that leverages a multimodal agent - powered by a novel conversational architecture using a multimodal large language…

Search engines enable the retrieval of unknown information with texts. However, traditional methods fall short when it comes to understanding unfamiliar visual content, such as identifying an object that the model has never seen before.…

Computer Vision and Pattern Recognition · Computer Science 2024-10-29 Zhixin Zhang , Yiyuan Zhang , Xiaohan Ding , Xiangyu Yue

Long-form video understanding presents significant challenges due to extensive temporal-spatial complexity and the difficulty of question answering under such extended contexts. While Large Language Models (LLMs) have demonstrated…

Computer Vision and Pattern Recognition · Computer Science 2025-11-04 Xiaoyi Zhang , Zhaoyang Jia , Zongyu Guo , Jiahao Li , Bin Li , Houqiang Li , Yan Lu

Recent advancements on Large Language Models (LLMs) enable AI Agents to automatically generate and execute multi-step plans to solve complex tasks. However, since LLM's content generation process is hardly controllable, current LLM-based…

Machine Learning · Computer Science 2024-08-13 Zelong Li , Wenyue Hua , Hao Wang , He Zhu , Yongfeng Zhang

Large Language Models (LLMs) are revolutionizing industries by enhancing efficiency, scalability, and innovation. This paper investigates the potential of LLMs in automating Computer-Aided Design (CAD) workflows, by integrating FreeCAD with…

Human-Computer Interaction · Computer Science 2025-08-05 Sumit Kumar , Sarthak Kapoor , Harsh Vardhan , Yao Zhao

We explore the integration of large language models (LLMs) into visual analytics (VA) systems to transform their capabilities through intuitive natural language interactions. We survey current research directions in this emerging field,…

Human-Computer Interaction · Computer Science 2025-07-01 Maeve Hutchinson , Radu Jianu , Aidan Slingsby , Pranava Madhyastha

Immersive virtual reality (VR) offers affordances that may reduce cognitive complexity in binary reverse engineering (RE), enabling embodied and external cognition to augment the RE process through enhancing memory, hypothesis testing, and…

Human-Computer Interaction · Computer Science 2025-08-20 Dennis Brown , Samuel Mulder