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High-quality textual training data is essential for the success of multimodal data processing tasks, yet outputs from image captioning models like BLIP and GIT often contain errors and anomalies that are difficult to rectify using…

计算与语言 · 计算机科学 2025-02-25 Elyas Meguellati , Nardiena Pratama , Shazia Sadiq , Gianluca Demartini

Large Language Models (LLMs) have drawn a lot of attention due to their strong performance on a wide range of natural language tasks, since the release of ChatGPT in November 2022. LLMs' ability of general-purpose language understanding and…

计算与语言 · 计算机科学 2025-03-25 Shervin Minaee , Tomas Mikolov , Narjes Nikzad , Meysam Chenaghlu , Richard Socher , Xavier Amatriain , Jianfeng Gao

Large Language Models (LLMs) have shown impressive capabilities across a wide variety of tasks. However, they still face challenges with long-horizon planning. To study this, we propose path planning tasks as a platform to evaluate LLMs'…

人工智能 · 计算机科学 2024-06-24 Mohamed Aghzal , Erion Plaku , Ziyu Yao

By integrating the perception capabilities of multimodal encoders with the generative power of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), exemplified by GPT-4V, have achieved great success in various multimodal…

计算机视觉与模式识别 · 计算机科学 2025-08-18 Wenbin An , Jiahao Nie , Yaqiang Wu , Feng Tian , Shijian Lu , Qinghua Zheng

Multimodal Large Language Models (MLLMs) are gaining increasing popularity in both academia and industry due to their remarkable performance in various applications such as visual question answering, visual perception, understanding, and…

计算与语言 · 计算机科学 2024-09-09 Jian Li , Weiheng Lu , Hao Fei , Meng Luo , Ming Dai , Min Xia , Yizhang Jin , Zhenye Gan , Ding Qi , Chaoyou Fu , Ying Tai , Wankou Yang , Yabiao Wang , Chengjie Wang

In the past year, MultiModal Large Language Models (MM-LLMs) have undergone substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs via cost-effective training strategies. The resulting models not only…

计算与语言 · 计算机科学 2024-05-29 Duzhen Zhang , Yahan Yu , Jiahua Dong , Chenxing Li , Dan Su , Chenhui Chu , Dong Yu

The introduction of ChatGPT has led to a significant increase in the utilization of Large Language Models (LLMs) for addressing downstream tasks. There's an increasing focus on cost-efficient training and deployment within this context.…

Simulating learner actions helps stress-test open-ended interactive learning environments and prototype new adaptations before deployment. While recent studies show the promise of using large language models (LLMs) for simulating human…

人工智能 · 计算机科学 2024-10-15 Amogh Mannekote , Adam Davies , Jina Kang , Kristy Elizabeth Boyer

Large language models (LLMs) have shown remarkable abilities to generate code, however their ability to develop software for embedded systems, which requires cross-domain knowledge of hardware and software has not been studied. In this…

Large language models and multimodal large language models have revolutionized artificial intelligence recently. An increasing number of regions are now embracing these advanced technologies. Within this context, robot coding education is…

Large language models (LLMs), especially generative pre-trained transformers (GPTs), have recently demonstrated outstanding ability in information comprehension and problem-solving. This has motivated many studies in applying LLMs to…

机器学习 · 计算机科学 2024-05-21 Han Zhang , Akram Bin Sediq , Ali Afana , Melike Erol-Kantarci

Recent developments in multimodal methodologies have marked the beginning of an exciting era for models adept at processing diverse data types, encompassing text, audio, and visual content. Models like GPT-4V, which merge computer vision…

Large language models (LLMs) are increasingly embedded in AI-based tutoring systems. Can they faithfully model novice reasoning and metacognitive judgments? Existing evaluations emphasize problem-solving accuracy, overlooking the fragmented…

计算与语言 · 计算机科学 2026-05-12 Conrad Borchers , Jill-Jênn Vie , Roger Azevedo

The integration of Large Language Models (LLMs) like GPT-4o into robotic systems represents a significant advancement in embodied artificial intelligence. These models can process multi-modal prompts, enabling them to generate more…

机器人学 · 计算机科学 2024-09-10 Wenxiao Zhang , Xiangrui Kong , Conan Dewitt , Thomas Braunl , Jin B. Hong

Large language models (LLMs) have shown great potential for the automatic generation of feedback in a wide range of computing contexts. However, concerns have been voiced around the privacy and ethical implications of sending student work…

计算与语言 · 计算机科学 2024-05-09 Charles Koutcheme , Nicola Dainese , Sami Sarsa , Arto Hellas , Juho Leinonen , Paul Denny

Large Language Models (LLMs) have demonstrated exceptional capabilities in various natural language tasks, often achieving performances that surpass those of humans. Despite these advancements, the domain of mathematics presents a…

计算与语言 · 计算机科学 2024-04-02 Ankit Satpute , Noah Giessing , Andre Greiner-Petter , Moritz Schubotz , Olaf Teschke , Akiko Aizawa , Bela Gipp

Large Language Models (LLMs) hold promise as dynamic instructional aids. Yet, it remains unclear whether LLMs can replicate the adaptivity of intelligent tutoring systems (ITS)--where student knowledge and pedagogical strategies are…

计算与语言 · 计算机科学 2025-04-09 Conrad Borchers , Tianze Shou

The deployment of autonomous robots in various domains has raised significant concerns about their trustworthiness and accountability. This study explores the potential of Large Language Models (LLMs) in analyzing ROS 2 logs generated by…

Multimodal Large Language Models (MLLMs) are widely regarded as crucial in the exploration of Artificial General Intelligence (AGI). The core of MLLMs lies in their capability to achieve cross-modal alignment. To attain this goal, current…

计算与语言 · 计算机科学 2024-11-26 Fei Zhao , Taotian Pang , Chunhui Li , Zhen Wu , Junjie Guo , Shangyu Xing , Xinyu Dai

Large language models (LLMs) and prompt engineering hold significant potential for advancing computer programming education through personalized instruction. This paper explores this potential by investigating three critical research…

人工智能 · 计算机科学 2024-07-09 Tianyu Wang , Nianjun Zhou , Zhixiong Chen