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Prompt-based learning has been demonstrated as a compelling paradigm contributing to large language models' tremendous success (LLMs). Inspired by their success in language tasks, existing research has leveraged LLMs in embodied instruction…

The recent advancements introduced by Large Language Models (LLMs) have transformed how Artificial Intelligence (AI) can support complex, real world tasks, pushing research outside the text boundaries towards multi modal contexts and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Federico Toschi , Nicolò Brunello , Andrea Sassella , Vincenzo Scotti , Mark James Carman

Large language models (LLMs) are increasingly being used as decision aids. However, users have diverse values and preferences that can affect their decision-making, which requires novel methods for LLM alignment and personalization.…

Computation and Language · Computer Science 2025-07-15 Bharadwaj Ravichandran , David Joy , Paul Elliott , Brian Hu , Jadie Adams , Christopher Funk , Emily Veenhuis , Anthony Hoogs , Arslan Basharat

With the development of Large Language Models (LLM), numerous prompts have been proposed, each with a rich set of features and their own merits. This paper summarizes the prompt words for large language models (LLMs), categorizing them into…

Computation and Language · Computer Science 2024-04-17 Chenggian Ma , Xiangyu Zhao , Chunhui Zhang , Yanzhao Qin , Wentao Zhang

Layout generation is the keystone in achieving automated graphic design, requiring arranging the position and size of various multi-modal design elements in a visually pleasing and constraint-following manner. Previous approaches are either…

Computer Vision and Pattern Recognition · Computer Science 2024-11-27 Tao Yang , Yingmin Luo , Zhongang Qi , Yang Wu , Ying Shan , Chang Wen Chen

The Multi-Modal Large Language Model (MLLM) refers to an extension of the Large Language Model (LLM) equipped with the capability to receive and infer multi-modal data. Spatial awareness stands as one of the crucial abilities of MLLM,…

Artificial Intelligence · Computer Science 2023-11-02 Yongqiang Zhao , Zhenyu Li , Zhi Jin , Feng Zhang , Haiyan Zhao , Chengfeng Dou , Zhengwei Tao , Xinhai Xu , Donghong Liu

Most Human-Machine Interaction (HMI) research overlooks the maneuvering needs of passengers in autonomous driving (AD). Natural language offers an intuitive interface, yet translating passenger open-ended instructions into control signals,…

Robotics · Computer Science 2026-04-10 Jiawei Liu , Xun Gong , Fen Fang , Muli Yang , Bohao Qu , Yunfeng Hu , Hong Chen , Xulei Yang , Qing Guo

Interaction with Large Language Models (LLMs) is primarily carried out via prompting. A prompt is a natural language instruction designed to elicit certain behaviour or output from a model. In theory, natural language prompts enable…

Human-Computer Interaction · Computer Science 2024-03-15 Michael Desmond , Michelle Brachman

Large language models (LLMs) demonstrate extraordinary abilities in a wide range of natural language processing (NLP) tasks. In this paper, we show that, beyond text understanding capability, LLMs are capable of processing text layouts that…

Computation and Language · Computer Science 2024-08-29 Weiming Li , Manni Duan , Dong An , Yan Shao

Usability evaluation is an essential method to support the design of effective and intuitive user interfaces (UIs). However, it commonly relies on resource-intensive, expert-driven methods, which limit its accessibility, especially for…

Software Engineering · Computer Science 2026-04-13 Sebastian Lubos , Alexander Felfernig , Damian Garber , Gerhard Leitner , Julian Schwazer , Manuel Henrich

With the rapid adoption of Large Language Models (LLMs), LLM-adapters have become increasingly common, providing lightweight specialization of large-scale models. Serving hundreds or thousands of these adapters on a single GPU allows…

Recently, there has been considerable attention towards leveraging large language models (LLMs) to enhance decision-making processes. However, aligning the natural language text instructions generated by LLMs with the vectorized operations…

Robotics · Computer Science 2024-02-23 Jinyi Liu , Yifu Yuan , Jianye Hao , Fei Ni , Lingzhi Fu , Yibin Chen , Yan Zheng

Multi-modal Large Language Models (MLLMs) have advanced greatly in general tasks. However, they still face challenges in geometric reasoning, a task that requires synergistic integration of visual recognition proficiency and complex…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Zhihao Li , Yao Du , Yang Liu , Yan Zhang , Yufang Liu , Mengdi Zhang , Xunliang Cai , Charles Ling , Boyu Wang

Multimodal Large Language Model (MLLM) has recently garnered attention as a prominent research focus. By harnessing powerful LLM, it facilitates a transition of conversational generative AI from unimodal text to performing multimodal tasks.…

Computer Vision and Pattern Recognition · Computer Science 2024-10-22 Xuechen Guo , Wenhao Chai , Shi-Yan Li , Gaoang Wang

As large language models (LLMs) like ChatGPT exhibited unprecedented machine intelligence, it also shows great performance in assisting hardware engineers to realize higher-efficiency logic design via natural language interaction. To…

Artificial Intelligence · Computer Science 2025-10-14 Kaiyan Chang , Ying Wang , Haimeng Ren , Mengdi Wang , Shengwen Liang , Yinhe Han , Huawei Li , Xiaowei Li

Large Language Models-Cognitive Assistants (LLM-CAs) can enhance Quality Management Systems (QMS) in manufacturing, fostering continuous process improvement and knowledge management. However, there is no human-centred software architecture…

Software Engineering · Computer Science 2026-03-18 Marcos Galdino , Johanna Grahl , Tobias Hamann , Anas Abdelrazeq , Ingrid Isenhardt

Feature selection is a crucial step in large-scale industrial machine learning systems, directly affecting model accuracy, efficiency, and maintainability. Traditional feature selection methods rely on labeled data and statistical…

The development of architecture specifications is an initial and fundamental stage of the integrated circuit (IC) design process. Traditionally, architecture specifications are crafted by experienced chip architects, a process that is not…

Hardware Architecture · Computer Science 2024-01-25 Mengming Li , Wenji Fang , Qijun Zhang , Zhiyao Xie

The advantages of pre-trained large language models (LLMs) are apparent in a variety of language processing tasks. But can a language model's knowledge be further harnessed to effectively disambiguate objects and navigate decision-making…

Robotics · Computer Science 2024-01-09 Connie Jiang , Yiqing Xu , David Hsu

Humans naturally understand 3D spatial relationships, enabling complex reasoning like predicting collisions of vehicles from different directions. Current large multimodal models (LMMs), however, lack of this capability of 3D spatial…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Wufei Ma , Luoxin Ye , Celso M de Melo , Jieneng Chen , Alan Yuille