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相关论文: Choice Over Control: How Users Write with Large La…

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Prompt engineering has emerged as an indispensable technique for extending the capabilities of large language models (LLMs) and vision-language models (VLMs). This approach leverages task-specific instructions, known as prompts, to enhance…

人工智能 · 计算机科学 2025-03-18 Pranab Sahoo , Ayush Kumar Singh , Sriparna Saha , Vinija Jain , Samrat Mondal , Aman Chadha

Text-to-image generative models have demonstrated remarkable capabilities in generating high-quality images based on textual prompts. However, crafting prompts that accurately capture the user's creative intent remains challenging. It often…

人机交互 · 计算机科学 2023-04-20 Stephen Brade , Bryan Wang , Mauricio Sousa , Sageev Oore , Tovi Grossman

While Chain of Thought (CoT) prompting approaches have significantly consolidated the reasoning capabilities of large language models (LLMs), they still face limitations that require extensive human effort or have performance needs to be…

计算与语言 · 计算机科学 2025-06-02 Kangyang Luo , Zichen Ding , Zhenmin Weng , Lingfeng Qiao , Meng Zhao , Xiang Li , Di Yin , Jinlong Shu

Large Language Models (LLMs) are now capable of generating highly fluent, human-like text. They enable many applications, but also raise concerns such as large scale spam, phishing, or academic misuse. While much work has focused on…

计算与语言 · 计算机科学 2026-04-16 Swati Rallapalli , Shannon Gallagher , Ronald Yurko , Tyler Brooks , Chuck Loughin , Michele Sezgin , Violet Turri

As Large Language Models (LLMs) grow increasingly adept at managing complex tasks, the evaluation set must keep pace with these advancements to ensure it remains sufficiently discriminative. Item Discrimination (ID) theory, which is widely…

计算与语言 · 计算机科学 2024-10-08 Fan Lin , Shuyi Xie , Yong Dai , Wenlin Yao , Tianjiao Lang , Zishan Xu , Zhichao Hu , Xiao Xiao , Yuhong Liu , Yu Zhang

As Large Language Models (LLMs) are nondeterministic, the same input can generate different outputs, some of which may be incorrect or hallucinated. If run again, the LLM may correct itself and produce the correct answer. Unfortunately,…

人机交互 · 计算机科学 2024-05-10 Yoonjoo Lee , Kihoon Son , Tae Soo Kim , Jisu Kim , John Joon Young Chung , Eytan Adar , Juho Kim

Pretrained large language models (LLMs) are increasingly utilized across a wide range of natural language processing (NLP) tasks due to their impressive capabilities as few-shot learners. Recent techniques, such as chain-of-thought (CoT)…

机器学习 · 计算机科学 2024-12-02 Kamesh R

As large language models (LLMs) become more common in educational tools and programming environments, questions arise about how these systems should interact with users. This study investigates how different interaction styles with…

人机交互 · 计算机科学 2025-07-08 Kai Deng

Large Language Models (LLMs) are highly sensitive to prompts, including additional context provided therein. As LLMs grow in capability, understanding their prompt-sensitivity becomes increasingly crucial for ensuring reliable and robust…

计算与语言 · 计算机科学 2024-08-23 Sotiris Anagnostidis , Jannis Bulian

Whether in agentic workflows, social studies, or chat settings, large language models (LLMs) are increasingly being asked to replace humans in choosing which goals to pursue, rather than completing predefined tasks. However, the assumption…

计算与语言 · 计算机科学 2026-05-14 Gaia Molinaro , Dave August , Danielle Perszyk , Anne G. E. Collins

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

Large Language Models (LLMs) have shown remarkable capabilities in manipulating natural language across multiple applications, but their ability to handle simple reasoning tasks is often questioned. In this work, we aim to provide a…

计算与语言 · 计算机科学 2025-05-05 Alessandro Raganato , Rafael Peñaloza , Marco Viviani , Gabriella Pasi

Large Language Models (LLMs) have demonstrated strong capabilities in natural language understanding and reasoning. However, their ability to perform exact, deterministic computation remains unclear. In this work, we systematically evaluate…

人工智能 · 计算机科学 2026-05-08 Hongkun Yu

Large language models(LLMs) like Gemini are becoming common tools for supporting student writing. But most of their feedback is based only on the final essay missing important context about how that text was written. In this paper, we…

计算与语言 · 计算机科学 2025-06-11 Samra Zafar , Shaheer Minhas , Syed Ali Hassan Zaidi , Arfa Naeem , Zahra Ali

Large language models (LLMs) are increasingly utilized in various complex reasoning tasks due to their excellent instruction following capability. However, the model's performance is highly dependent on the open-ended characteristics of the…

计算与语言 · 计算机科学 2026-04-28 Zhenzhen Huang , Chaoning Zhang , Fachrina Dewi Puspitasari , Jiaquan Zhang , Yitian Zhou , Shuxu Chen , Yang Yang

Most large language models (LLMs) are sensitive to prompts, and another synonymous expression or a typo may lead to unexpected results for the model. Composing an optimal prompt for a specific demand lacks theoretical support and relies…

计算与语言 · 计算机科学 2024-06-18 Zhenyu Zhang , Bingguang Hao , Jinpeng Li , Zekai Zhang , Dongyan Zhao

In this paper, we demonstrate how studying the rhetorics of ChatGPT prompt writing on social media can promote critical AI literacies. Prompt writing is the process of writing instructions for generative AI tools like ChatGPT to elicit…

计算机与社会 · 计算机科学 2025-11-04 Anuj Gupta , Ann Shivers-McNair

Narrative-driven recommenders aim to provide personalized suggestions for user requests expressed in free-form text such as "I want to watch a thriller with a mind-bending story, like Shutter Island." Although large language models (LLMs)…

信息检索 · 计算机科学 2024-10-18 Lukas Eberhard , Thorsten Ruprechter , Denis Helic

Large Language Models (LLMs) can generate text by transferring style attributes like formality resulting in formal or informal text. However, instructing LLMs to generate text that when spoken, is more intelligible in an acoustically…

计算与语言 · 计算机科学 2024-08-09 Anupama Chingacham , Miaoran Zhang , Vera Demberg , Dietrich Klakow

Prior research shows that how students engage with Large Language Models (LLMs) influences their problem-solving and understanding, reinforcing the need to support productive LLM-uses that promote learning. This study evaluates the impact…

计算机与社会 · 计算机科学 2025-08-25 Jerome Brender , Laila El-Hamamsy , Kim Uittenhove , Francesco Mondada , Engin Bumbacher