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We introduce V-Agent, a novel multi-agent platform designed for advanced video search and interactive user-system conversations. By fine-tuning a vision-language model (VLM) with a small video preference dataset and enhancing it with a…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 SunYoung Park , Jong-Hyeon Lee , Youngjune Kim , Daegyu Sung , Younghyun Yu , Young-rok Cha , Jeongho Ju

The rapid advancement of Large Vision-Language models (LVLMs) has demonstrated a spectrum of emergent capabilities. Nevertheless, current models only focus on the visual content of a single scenario, while their ability to associate…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Yatai Ji , Shilong Zhang , Jie Wu , Peize Sun , Weifeng Chen , Xuefeng Xiao , Sidi Yang , Yujiu Yang , Ping Luo

Large Vision Language Models (LVLMs) have shown strong capabilities in understanding and analyzing visual scenes across various domains. However, in the context of autonomous driving, their limited comprehension of 3D environments restricts…

Computer Vision and Pattern Recognition · Computer Science 2025-05-02 Jannik Lübberstedt , Esteban Rivera , Nico Uhlemann , Markus Lienkamp

Integrating Large Language Models (LLMs) into autonomous agents marks a significant shift in the research landscape by offering cognitive abilities that are competitive with human planning and reasoning. This paper explores the…

Software Engineering · Computer Science 2025-07-21 Junda He , Christoph Treude , David Lo

Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves…

Computer Vision and Pattern Recognition · Computer Science 2023-07-25 Yining Hong , Haoyu Zhen , Peihao Chen , Shuhong Zheng , Yilun Du , Zhenfang Chen , Chuang Gan

Despite the remarkable progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, their application to complex 3D scene manipulation remains underexplored. In this paper, we bridge this critical gap by tackling three…

Computer Vision and Pattern Recognition · Computer Science 2026-01-08 Zhengfei Kuang , Rui Lin , Long Zhao , Gordon Wetzstein , Saining Xie , Sanghyun Woo

Large Language Model (LLM) Agents have recently garnered increasing interest yet they are limited in their ability to learn from trial and error, a key element of intelligent behavior. In this work, we argue that the capacity to learn new…

Artificial Intelligence · Computer Science 2024-08-09 Haiteng Zhao , Chang Ma , Guoyin Wang , Jing Su , Lingpeng Kong , Jingjing Xu , Zhi-Hong Deng , Hongxia Yang

Autonomous Driving Systems (ADSs) are revolutionizing transportation by reducing human intervention, improving operational efficiency, and enhancing safety. Large Language Models (LLMs) have been integrated into ADSs to support high-level…

Multiagent Systems · Computer Science 2025-10-15 Yaozu Wu , Dongyuan Li , Yankai Chen , Renhe Jiang , Henry Peng Zou , Wei-Chieh Huang , Yangning Li , Liancheng Fang , Zhen Wang , Philip S. Yu

Medical Decision-Making (MDM) is a multi-faceted process that requires clinicians to assess complex multi-modal patient data patient, often collaboratively. Large Language Models (LLMs) promise to streamline this process by synthesizing…

GUIs have long been central to human-computer interaction, providing an intuitive and visually-driven way to access and interact with digital systems. The advent of LLMs, particularly multimodal models, has ushered in a new era of GUI…

Artificial Intelligence · Computer Science 2025-05-07 Chaoyun Zhang , Shilin He , Jiaxu Qian , Bowen Li , Liqun Li , Si Qin , Yu Kang , Minghua Ma , Guyue Liu , Qingwei Lin , Saravan Rajmohan , Dongmei Zhang , Qi Zhang

Large language models (LLMs) can generate fluent dialogue, but prior works lack situational grounding, dynamic strategy control, and evaluation aligned with clinical standards in motivational interviewing (MI). We introduce StoryMI, a…

Computation and Language · Computer Science 2026-05-28 Qingyu Meng , Min Chen , Dingming Liu , Yifan Mo , Yue Su , Xin Sun , Koen Hindriks , Jiahuan Pei

Large Language Models (LLMs) have revolutionized the simulation of agent societies, enabling autonomous planning, memory formation, and social interactions. However, existing frameworks often overlook systematic evaluations for event…

Artificial Intelligence · Computer Science 2025-09-17 Yuyang Tian , Shunqiang Mao , Wenchang Gao , Lanlan Qiu , Tianxing He

A wide range of real-world applications is characterized by their symbolic nature, necessitating a strong capability for symbolic reasoning. This paper investigates the potential application of Large Language Models (LLMs) as symbolic…

Computation and Language · Computer Science 2024-01-18 Meng Fang , Shilong Deng , Yudi Zhang , Zijing Shi , Ling Chen , Mykola Pechenizkiy , Jun Wang

With the rapid advancement of Vision-Language Models (VLMs), GUI-based mobile agents have emerged as a key development direction for intelligent mobile systems. However, existing agent models continue to face significant challenges in…

Multiagent Systems · Computer Science 2025-09-03 Cheng Zhang , Erhu Feng , Xi Zhao , Yisheng Zhao , Wangbo Gong , Jiahui Sun , Dong Du , Zhichao Hua , Yubin Xia , Haibo Chen

Large language models (LLMs) exhibit strong symbolic and compositional reasoning, yet they struggle with time series question answering as the data is typically transformed into an LLM-compatible modality, e.g., serialized text, plotted…

Artificial Intelligence · Computer Science 2026-04-08 Penghang Liu , Elizabeth Fons , Annita Vapsi , Mohsen Ghassemi , Svitlana Vyetrenko , Daniel Borrajo , Vamsi K. Potluru , Manuela Veloso

Multimodal large language models (MLLMs) that integrate visual and textual reasoning leverage chain-of-thought (CoT) prompting to tackle complex visual tasks, yet continue to exhibit visual hallucinations and an over-reliance on textual…

Computer Vision and Pattern Recognition · Computer Science 2025-10-24 Jing Bi , Guangyu Sun , Ali Vosoughi , Chen Chen , Chenliang Xu

Long-form video understanding remains a fundamental challenge for current Video Large Language Models. Most existing models rely on static reasoning over uniformly sampled frames, which weakens temporal localization and leads to substantial…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Chenglin Li , Qianglong Chen , Feng Han , Yikun Wang , Xingxi Yin , Yan Gong , Ruilin Li , Yin Zhang , Jiaqi Wang

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

This work investigates whether knowledge-driven large language model (LLM)-based storytelling can support purposeful narrative interaction with a digital companion for older adults. To address known limitations of LLMs, including…

Artificial Intelligence · Computer Science 2026-05-12 Jayalakshmi Baskar , Vera C. Kaelin , Kaan Kilic , Helena Lindgren

Recent advancements in Large Language Models (LLMs) have led to the development of intelligent LLM-based agents capable of interacting with graphical user interfaces (GUIs). These agents demonstrate strong reasoning and adaptability,…

Artificial Intelligence · Computer Science 2025-04-16 Wenjia Jiang , Yangyang Zhuang , Chenxi Song , Xu Yang , Joey Tianyi Zhou , Chi Zhang
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