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Large language models (LLMs), when guided by explicit textual plans, can perform reliable step-by-step reasoning during problem-solving. However, generating accurate and effective textual plans remains challenging due to LLM hallucinations…

Computation and Language · Computer Science 2026-01-01 Sijia Chen , Di Niu

Large language models have shown their remarkable capabilities as a general interface for various language-related applications. Motivated by this, we target to build a unified interface for completing many vision-language tasks including…

Computer Vision and Pattern Recognition · Computer Science 2023-11-08 Jun Chen , Deyao Zhu , Xiaoqian Shen , Xiang Li , Zechun Liu , Pengchuan Zhang , Raghuraman Krishnamoorthi , Vikas Chandra , Yunyang Xiong , Mohamed Elhoseiny

In modern industrial production, multiple robots often collaborate to complete complex manufacturing tasks. Large language models (LLMs), with their strong reasoning capabilities, have shown potential in coordinating robots for simple…

Robotics · Computer Science 2026-03-04 Xiangyu Su , Juzhan Xu , Oliver van Kaick , Kai Xu , Ruizhen Hu

Colors play a crucial role in the design of vector graphic documents by enhancing visual appeal, facilitating communication, improving usability, and ensuring accessibility. In this context, color recommendation involves suggesting…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Ding Xia , Naoto Inoue , Qianru Qiu , Kotaro Kikuchi

Graphical User Interface (GUI) Agents, powered by multimodal large language models (MLLMs), have shown great potential for task automation on computing devices such as computers and mobile phones. However, existing agents face challenges in…

Artificial Intelligence · Computer Science 2025-01-09 Yuhang Liu , Pengxiang Li , Zishu Wei , Congkai Xie , Xueyu Hu , Xinchen Xu , Shengyu Zhang , Xiaotian Han , Hongxia Yang , Fei Wu

Our research investigates the capability of modern multimodal reasoning models, powered by Large Language Models (LLMs), to facilitate vision-powered assistants for multi-step daily activities. Such assistants must be able to 1) encode…

Computer Vision and Pattern Recognition · Computer Science 2024-08-14 Mrinal Verghese , Brian Chen , Hamid Eghbalzadeh , Tushar Nagarajan , Ruta Desai

Generating lifelike human motions from descriptive texts has experienced remarkable research focus in the recent years, propelled by the emerging requirements of digital humans.Despite impressive advances, existing approaches are often…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Yuan Wang , Di Huang , Yaqi Zhang , Wanli Ouyang , Jile Jiao , Xuetao Feng , Yan Zhou , Pengfei Wan , Shixiang Tang , Dan Xu

Large language models (LLMs) have proven their remarkable versatility in handling a comprehensive range of language-centric applications. To expand LLMs' capabilities to a broader spectrum of modal inputs, multimodal large language models…

Computer Vision and Pattern Recognition · Computer Science 2023-12-07 Qiang Zhou , Zhibin Wang , Wei Chu , Yinghui Xu , Hao Li , Yuan Qi

Large Language Model (LLM)-based robotic assembly assistance has gained significant research attention. It requires the injection of domain-specific knowledge to guide the assembly process through natural language interaction with humans.…

Robotics · Computer Science 2026-03-03 Qi Zheng , Chaoran Zhang , Zijian Liang , EnTe Lin , Shubo Cui , Qinghongbing Xie , Zhaobo Xu , Long Zeng

We present an interactive visual framework named InternGPT, or iGPT for short. The framework integrates chatbots that have planning and reasoning capabilities, such as ChatGPT, with non-verbal instructions like pointing movements that…

Computer Vision and Pattern Recognition · Computer Science 2023-06-05 Zhaoyang Liu , Yinan He , Wenhai Wang , Weiyun Wang , Yi Wang , Shoufa Chen , Qinglong Zhang , Zeqiang Lai , Yang Yang , Qingyun Li , Jiashuo Yu , Kunchang Li , Zhe Chen , Xue Yang , Xizhou Zhu , Yali Wang , Limin Wang , Ping Luo , Jifeng Dai , Yu Qiao

Academic writing skills are crucial for students' success, but can feel overwhelming without proper guidance and practice, particularly when writing in a second language. Traditionally, students ask instructors or search dictionaries, which…

Artificial Intelligence · Computer Science 2025-06-24 Fumian Chen , Sotheara Veng , Joshua Wilson , Xiaoming Li , Hui Fang

Effective planning is essential for the success of any task, from organizing a vacation to routing autonomous vehicles and developing corporate strategies. It involves setting goals, formulating plans, and allocating resources to achieve…

Artificial Intelligence · Computer Science 2024-09-04 Haoming Li , Zhaoliang Chen , Jonathan Zhang , Fei Liu

When humans face problems beyond their immediate capabilities, they rely on tools, providing a promising paradigm for improving visual reasoning in multimodal large language models (MLLMs). Effective reasoning, therefore, hinges on knowing…

Artificial Intelligence · Computer Science 2026-01-29 Mingyang Song , Haoyu Sun , Jiawei Gu , Linjie Li , Luxin Xu , Ranjay Krishna , Yu Cheng

Multimodal large language models (MLLMs) have emerged as a prominent area of interest within the research community, given their proficiency in handling and reasoning with non-textual data, including images and videos. This study seeks to…

Computer Vision and Pattern Recognition · Computer Science 2024-11-12 Zhenhua Xu , Yujia Zhang , Enze Xie , Zhen Zhao , Yong Guo , Kwan-Yee. K. Wong , Zhenguo Li , Hengshuang Zhao

Large Language Models (LLMs) have demonstrated exceptional proficiency in text understanding and embedding tasks. However, their potential in multimodal representation, particularly for item-to-item (I2I) recommendations, remains…

Information Retrieval · Computer Science 2025-01-22 Chao Zhang , Haoxin Zhang , Shiwei Wu , Di Wu , Tong Xu , Xiangyu Zhao , Yan Gao , Yao Hu , Enhong Chen

Multimodal Large Language Models (MLLMs) show promise for medical applications, yet progress in dermatology lags due to limited training data, narrow task coverage, and lack of clinically-grounded supervision that mirrors expert diagnostic…

Computation and Language · Computer Science 2026-01-06 Jinghan Ru , Siyuan Yan , Yuguo Yin , Yuexian Zou , Zongyuan Ge

Large language models(LLMs), with their powerful language generation and reasoning capabilities, have already achieved notable success in many domains, e.g., math and code generation. However, they often fall short when tackling real-life…

Artificial Intelligence · Computer Science 2025-06-03 Jie Feng , Tianhui Liu , Yuwei Du , Siqi Guo , Yuming Lin , Yong Li

The rise of large language models (LLMs) has made natural language-driven route planning an emerging research area that encompasses rich user objectives. Current research exhibits two distinct approaches: direct route planning using…

Artificial Intelligence · Computer Science 2025-09-17 Liangqi Yuan , Dong-Jun Han , Christopher G. Brinton , Sabine Brunswicker

The advent of large language models (LLMs) has opened up new opportunities in the field of mobile task automation. Their superior language understanding and reasoning capabilities allow users to automate complex and repetitive tasks.…

Human-Computer Interaction · Computer Science 2024-10-17 Sunjae Lee , Junyoung Choi , Jungjae Lee , Munim Hasan Wasi , Hojun Choi , Steven Y. Ko , Sangeun Oh , Insik Shin

While intelligent virtual assistants like Siri, Alexa, and Google Assistant have become ubiquitous in modern life, they still face limitations in their ability to follow multi-step instructions and accomplish complex goals articulated in…

Machine Learning · Computer Science 2023-12-13 Yanchu Guan , Dong Wang , Zhixuan Chu , Shiyu Wang , Feiyue Ni , Ruihua Song , Longfei Li , Jinjie Gu , Chenyi Zhuang