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Difficult decision-making problems abound in various disciplines and domains. The proliferation of generative techniques, especially large language models (LLMs), has excited interest in using them for decision support. However, LLMs cannot…

人工智能 · 计算机科学 2025-09-16 Boris Kovalerchuk , Brent D. Fegley

Multitask learning assumes that models capable of learning from multiple tasks can achieve better quality and efficiency via knowledge transfer, a key feature of human learning. Though, state of the art ML models rely on high customization…

机器学习 · 计算机科学 2022-11-17 Andrea Gesmundo , Jeff Dean

The rapid advancement of generative models has empowered modern AI systems to comprehend and produce highly sophisticated content, even achieving human-level performance in specific domains. However, these models are fundamentally…

Generative AI is quickly becoming an integral part of people's everyday workflows. Early evidence has shown that while generative AI can increase individual-level productivity, it does so at the cost of collective diversity, potentially…

人机交互 · 计算机科学 2026-04-07 Nathanael Jo , Manish Raghavan

Abstractive related work generation has attracted increasing attention in generating coherent related work that better helps readers grasp the background in the current research. However, most existing abstractive models ignore the inherent…

计算与语言 · 计算机科学 2023-05-24 Jiachang Liu , Qi Zhang , Chongyang Shi , Usman Naseem , Shoujin Wang , Ivor Tsang

Large Language Models (LLMs) have gained widespread popularity due to their ability to perform ad-hoc Natural Language Processing (NLP) tasks with a simple natural language prompt. Part of the appeal for LLMs is their approachability to the…

人机交互 · 计算机科学 2025-02-25 Aditi Mishra , Utkarsh Soni , Anjana Arunkumar , Jinbin Huang , Bum Chul Kwon , Chris Bryan

Auxiliary tasks facilitate learning in situations where data is scarce or the principal task of interest is extremely complex. This idea is primarily inspired by the improved generalization capability induced by solving multiple tasks…

机器学习 · 计算机科学 2025-07-28 Geri Skenderi , Luigi Capogrosso , Andrea Toaiari , Matteo Denitto , Franco Fummi , Simone Melzi

Prompt engineering is crucial for achieving reliable and effective outputs from large language models (LLMs), but its design requires specialized knowledge of prompting techniques and a deep understanding of target tasks. To address this…

计算与语言 · 计算机科学 2025-10-22 Yohei Ikenoue , Hitomi Tashiro , Shigeru Kuroyanagi

As Generative AI (GenAI) capabilities expand, understanding how to preserve and develop human expertise while leveraging AI's benefits becomes increasingly critical. Through empirical studies in two contexts -- survey article authoring in…

人机交互 · 计算机科学 2025-04-01 Alexa Siu , Raymond Fok

Test Driven Development (TDD) is one of the major practices of Extreme Programming for which incremental testing and refactoring trigger the code development. TDD has limited adoption in the industry, as it requires more code to be…

软件工程 · 计算机科学 2025-01-15 Moritz Mock , Jorge Melegati , Barbara Russo

The landscape of education is changing rapidly, shaped by emerging pedagogical approaches, technological innovations such as artificial intelligence (AI), and evolving societal expectations, all of which demand thorough evaluation of new…

Generative Artificial Intelligence (Generative AI) is a collection of AI technologies that can generate new information such as texts and images. With its strong capabilities, Generative AI has been actively studied in creative design…

人机交互 · 计算机科学 2025-02-04 Liuging Chen , Yaxuan Song , Jia Guo , Lingyun Sun , Peter Childs , Yuan Yin

The rapid advancements in Generative AI and Large Language Models promise to transform the way research is conducted, potentially offering unprecedented opportunities to augment scholarly workflows. However, effectively integrating AI into…

Can one inject new concepts into an already trained generative model, while respecting its existing structure and knowledge? We propose a new task - domain expansion - to address this. Given a pretrained generator and novel (but related)…

计算机视觉与模式识别 · 计算机科学 2023-04-18 Yotam Nitzan , Michaël Gharbi , Richard Zhang , Taesung Park , Jun-Yan Zhu , Daniel Cohen-Or , Eli Shechtman

Current generative AI models like ChatGPT, Claude, and Gemini are widely used for knowledge dissemination, task decomposition, and creative thinking. However, their linear interaction methods often force users to repeatedly compare and copy…

人机交互 · 计算机科学 2024-10-16 Rui Zhang , Ziyao Zhang , Fengliang Zhu , Jiajie Zhou , Anyi Rao

Collaborations with Generative AI often begin with a short prompt and end with an opaque output, leaving implicit who was involved, what task was being pursued, which resources were used, and which constraints should have shaped the…

人机交互 · 计算机科学 2026-05-29 Ngoc Luyen Le , Marie-Hélène Abel , Bertrand Laforge

With the rapid development of artificial intelligence technology, especially the increasingly widespread application of question-and-answer systems, high-quality question generation has become a key component in supporting the development…

计算与语言 · 计算机科学 2024-09-30 Zhenhong Zhang , Jiajing Chen , Weiyan Shi , Lingjie Yi , Chihang Wang , Qian Yu

An advantage of Large Language Models (LLMs) is their contextualization capability - providing different responses based on student inputs like solution strategy or prior discussion, to potentially better engage students than standard…

Designing effective task-level prompts is crucial for improving the performance of Large Language Models (LLMs). While prior work on instruction induction demonstrates that LLMs can infer better instructions with limited examples, existing…

计算与语言 · 计算机科学 2026-05-21 Po-Chun Chen , Hen-Hsen Huang , Hsin-Hsi Chen

Generative AI (GenAI) has fundamentally changed how knowledge workers, such as software developers, solve tasks and collaborate to build software products. Introducing innovative tools like ChatGPT and Copilot has created new opportunities…

软件工程 · 计算机科学 2024-05-06 Rasmus Ulfsnes , Nils Brede Moe , Viktoria Stray , Marianne Skarpen