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Recent breakthroughs in Large Language Models (LLMs), such as GPT-3 and Codex, now enable software developers to generate code based on a natural language prompt. Within computer science education, researchers are exploring the potential…

Computers and Society · Computer Science 2022-12-13 Stephen MacNeil , Andrew Tran , Juho Leinonen , Paul Denny , Joanne Kim , Arto Hellas , Seth Bernstein , Sami Sarsa

This study introduces an innovative framework that employs large language models (LLMs) to automate the design and generation of curricula for reinforcement learning (RL). As mobile networks evolve towards the 6G era, managing their…

Machine Learning · Computer Science 2024-10-31 Omar Erak , Omar Alhussein , Shimaa Naser , Nouf Alabbasi , De Mi , Sami Muhaidat

Virtual Labs offer valuable opportunities for hands-on, inquiry-based science learning, yet teachers often struggle to adapt them to fit their instructional goals. Third-party materials may not align with classroom needs, and developing…

Computation and Language · Computer Science 2025-10-09 R. Alexander Knipper , Indrani Dey , Souvika Sarkar , Hari Narayanan , Sadhana Puntambekar , Santu Karmaker

Large-scale Vision Language Models (LVLMs) exhibit advanced capabilities in tasks that require visual information, including object detection. These capabilities have promising applications in various industrial domains, such as autonomous…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Haruki Sakajo , Hiroshi Takato , Hiroshi Tsutsui , Komei Soda , Hidetaka Kamigaito , Taro Watanabe

Recent studies have uncovered the potential of Large Language Models (LLMs) in addressing complex sequential decision-making tasks through the provision of high-level instructions. However, LLM-based agents lack specialization in tackling…

Artificial Intelligence · Computer Science 2024-05-28 Zihao Zhou , Bin Hu , Chenyang Zhao , Pu Zhang , Bin Liu

The integration of visual encoders and large language models (LLMs) has driven recent progress in multimodal large language models (MLLMs). However, the scarcity of high-quality instruction-tuning data for vision-language tasks remains a…

Computer Vision and Pattern Recognition · Computer Science 2024-02-06 Bin Wang , Fan Wu , Xiao Han , Jiahui Peng , Huaping Zhong , Pan Zhang , Xiaoyi Dong , Weijia Li , Wei Li , Jiaqi Wang , Conghui He

Generating accurate and consistent visual aids is a critical challenge in mathematics education, where visual representations like geometric shapes and functions play a pivotal role in enhancing student comprehension. This paper introduces…

Computation and Language · Computer Science 2024-11-11 Jeongwoo Lee , Kwangsuk Park , Jihyeon Park

Instruction-based language modeling has received significant attention in pretrained language models. However, the efficiency of instruction engineering remains low and hinders the development of instruction studies. Recent studies have…

Computation and Language · Computer Science 2023-10-27 Heng Yang , Ke Li

Advances in 3D generative AI have enabled the creation of physical objects from text prompts, but challenges remain in creating objects involving multiple component types. We present a pipeline that integrates 3D generative AI with…

Large Language Models have been increasingly employed in the creation of Virtual Assistants due to their ability to generate human-like text and handle complex inquiries. While these models hold great promise, challenges such as…

Computation and Language · Computer Science 2026-04-30 Dumitru Verşebeniuc , Martijn Elands , Sara Falahatkar , Chiara Magrone , Mohammad Falah , Martijn Boussé , Aki Härmä

The advent of immersive Virtual Reality applications has transformed various domains, yet their integration with advanced artificial intelligence technologies like Visual Language Models remains underexplored. This study introduces a…

Robotics · Computer Science 2024-08-06 Mikhail Konenkov , Artem Lykov , Daria Trinitatova , Dzmitry Tsetserukou

Large language models (LLMs) can perform a wide range of tasks by following natural language instructions, without the necessity of task-specific fine-tuning. Unfortunately, the performance of LLMs is greatly influenced by the quality of…

Computation and Language · Computer Science 2023-10-23 Zhihan Zhang , Shuohang Wang , Wenhao Yu , Yichong Xu , Dan Iter , Qingkai Zeng , Yang Liu , Chenguang Zhu , Meng Jiang

Recent large language models (LLMs) have demonstrated promising capabilities in modeling real-world knowledge and enhancing knowledge-based generation tasks. In this paper, we further explore the potential of using LLMs to aid in the design…

Robotics · Computer Science 2024-11-04 Weicheng Ma , Luyang Zhao , Chun-Yi She , Yitao Jiang , Alan Sun , Bo Zhu , Devin Balkcom , Soroush Vosoughi

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

Combining Large Language Models (LLMs) with Reinforcement Learning (RL) enables agents to interpret language instructions more effectively for task execution. However, LLMs typically lack direct perception of the physical environment, which…

Machine Learning · Computer Science 2026-03-25 Pengsen Liu , Maosen Zeng , Nan Tang , Kaiyuan Li , Jing-Cheng Pang , Yunan Liu , Yang Yu

This paper presents an innovative exploration of the application potential of large language models (LLM) in addressing the challenging task of automatically generating behavior trees (BTs) for complex tasks. The conventional manual BT…

Computation and Language · Computer Science 2024-01-17 Fu Li , Xueying Wang , Bin Li , Yunlong Wu , Yanzhen Wang , Xiaodong Yi

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

We explore the automatic generation of interactive, scenario-based lessons designed to train novice human tutors who teach middle school mathematics online. Employing prompt engineering through a Retrieval-Augmented Generation approach with…

Recently, there has been a surging interest in using large language models (LLMs) for Verilog code generation. However, the existing approaches are limited in terms of the quality of the generated Verilog code. To address such limitations,…

Machine Learning · Computer Science 2024-10-08 Bardia Nadimi , Hao Zheng

Despite the advances in text-to-image synthesis, particularly with diffusion models, generating visual instructions that require consistent representation and smooth state transitions of objects across sequential steps remains a formidable…

Computer Vision and Pattern Recognition · Computer Science 2024-06-11 Quynh Phung , Songwei Ge , Jia-Bin Huang