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Large transformer-based language models (LMs) trained on huge text corpora have shown unparalleled generation capabilities. However, controlling attributes of the generated language (e.g. switching topic or sentiment) is difficult without…

计算与语言 · 计算机科学 2020-03-04 Sumanth Dathathri , Andrea Madotto , Janice Lan , Jane Hung , Eric Frank , Piero Molino , Jason Yosinski , Rosanne Liu

The instruction-following ability of large language models enables humans to interact with AI agents in a natural way. However, when required to generate responses of a specific length, large language models often struggle to meet users'…

计算与语言 · 计算机科学 2024-10-02 Jiaming Li , Lei Zhang , Yunshui Li , Ziqiang Liu , yuelin bai , Run Luo , Longze Chen , Min Yang

Our work contributes to the fast-growing literature on the use of Large Language Models (LLMs) to perform graph-related tasks. In particular, we focus on usage scenarios that rely on the visual modality, feeding the model with a drawing of…

人工智能 · 计算机科学 2025-05-07 Walter Didimo , Fabrizio Montecchiani , Tommaso Piselli

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…

人机交互 · 计算机科学 2024-03-15 Michael Desmond , Michelle Brachman

Large language model (LLM) powered chatbots are primarily text-based today, and impose a large interactional cognitive load, especially for exploratory or sensemaking tasks such as planning a trip or learning about a new city. Because the…

人机交互 · 计算机科学 2023-12-04 Xiao Ma , Swaroop Mishra , Ariel Liu , Sophie Su , Jilin Chen , Chinmay Kulkarni , Heng-Tze Cheng , Quoc Le , Ed Chi

Advances in large language models (LLMs) are profoundly reshaping the field of human-robot interaction (HRI). While prior work has highlighted the technical potential of LLMs, few studies have systematically examined their human-centered…

机器人学 · 计算机科学 2026-02-18 Yufeng Wang , Yuan Xu , Anastasia Nikolova , Yuxuan Wang , Jianyu Wang , Chongyang Wang , Xin Tong

Large language models (LLMs) provide excellent text-generation capabilities, but standard prompting and generation methods generally do not lead to intentional or goal-directed agents and might necessitate considerable prompt tuning. This…

计算与语言 · 计算机科学 2023-12-01 Marwa Abdulhai , Isadora White , Charlie Snell , Charles Sun , Joey Hong , Yuexiang Zhai , Kelvin Xu , Sergey Levine

We report on a systematic, PRISMA-guided survey of research at the intersection of LLMs and visualization, with a particular focus on visio-verbal interaction -- where verbal and visual modalities converge to support data sense-making. The…

Large Language Models (LLMs) have demonstrated their remarkable capabilities in numerous fields. This survey focuses on how LLMs empower users, regardless of their technical background, to use human languages to automatically generate…

软件工程 · 计算机科学 2025-04-03 Nam Huynh , Beiyu Lin

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…

机器人学 · 计算机科学 2024-11-04 Weicheng Ma , Luyang Zhao , Chun-Yi She , Yitao Jiang , Alan Sun , Bo Zhu , Devin Balkcom , Soroush Vosoughi

Crafting effective prompts for code generation or editing with Large Language Models (LLMs) is not an easy task. Particularly, the absence of immediate, stable feedback during prompt crafting hinders effective interaction, as users are left…

人机交互 · 计算机科学 2024-05-14 Chen Zhu-Tian , Zeyu Xiong , Xiaoshuo Yao , Elena Glassman

In recent years, efforts have been made to use text information for better user profiling and item characterization in recommendations. However, text information can sometimes be of low quality, hindering its effectiveness for real-world…

人工智能 · 计算机科学 2024-02-15 Yingpeng Du , Ziyan Wang , Zhu Sun , Haoyan Chua , Hongzhi Liu , Zhonghai Wu , Yining Ma , Jie Zhang , Youchen Sun

The use of large language models (LLMs) in natural language processing (NLP) tasks is rapidly increasing, leading to changes in how researchers approach problems in the field. To fully utilize these models' abilities, a better understanding…

计算与语言 · 计算机科学 2023-11-07 Bishal Santra , Sakya Basak , Abhinandan De , Manish Gupta , Pawan Goyal

We propose a method that enables large language models (LLMs) to control embodied agents through the generation of control policies that directly map continuous observation vectors to continuous action vectors. At the outset, the LLMs…

人工智能 · 计算机科学 2026-02-25 Jônata Tyska Carvalho , Stefano Nolfi

This paper investigates the challenges of affect control in large language models (LLMs), focusing on their ability to express appropriate emotional states during extended dialogues. We evaluated state-of-the-art open-weight LLMs to assess…

人工智能 · 计算机科学 2025-03-05 Gino Franco Fazzi , Julie Skoven Hinge , Stefan Heinrich , Paolo Burelli

Large Language Models (LLMs) have upended decades of pedagogy in computing education. Students previously learned to code through \textit{writing} many small problems with less emphasis on code reading and comprehension. Recent research has…

The rapid advancement of Large Language Models (LLMs) has significantly influenced various domains, leveraging their exceptional few-shot and zero-shot learning capabilities. In this work, we aim to explore and understand the LLMs-based…

人工智能 · 计算机科学 2024-10-24 Dawei Li , Zhen Tan , Huan Liu

Large Language Models (LLMs) have emerged as formidable instruments capable of comprehending and producing human-like text. This paper explores the potential of LLMs, to shape user perspectives and subsequently influence their decisions on…

人工智能 · 计算机科学 2024-09-04 Ganesh Prasath Ramani , Shirish Karande , Santhosh V , Yash Bhatia

Large language models (LLMs) are shaping a new user interface (UI) paradigm in writing tools by enabling users to generate text through prompts. This paradigm shifts some creative control from the user to the system, thereby diminishing the…

人机交互 · 计算机科学 2024-03-05 Jiho Kim , Ray C. Flanagan , Noelle E. Haviland , ZeAi Sun , Souad N. Yakubu , Edom A. Maru , Kenneth C. Arnold

Language models are transforming the ways that their users engage with the world. Despite impressive capabilities, over-consumption of language model outputs risks propagating unchecked errors in the short-term and damaging human…