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Computational cognitive models, which formalize theories of cognition, enable researchers to quantify cognitive processes and arbitrate between competing theories by fitting models to behavioral data. Traditionally, these models are…

Machine Learning · Computer Science 2025-11-10 Milena Rmus , Akshay K. Jagadish , Marvin Mathony , Tobias Ludwig , Eric Schulz

In the rapidly evolving domain of Natural Language Generation (NLG) evaluation, introducing Large Language Models (LLMs) has opened new avenues for assessing generated content quality, e.g., coherence, creativity, and context relevance.…

Computation and Language · Computer Science 2024-06-13 Zhen Li , Xiaohan Xu , Tao Shen , Can Xu , Jia-Chen Gu , Yuxuan Lai , Chongyang Tao , Shuai Ma

Competency Questions (CQs) are a form of ontology functional requirements expressed as natural language questions. Inspecting CQs together with the axioms in an ontology provides critical insights into the intended scope and applicability…

Artificial Intelligence · Computer Science 2024-07-23 Reham Alharbi , Valentina Tamma , Floriana Grasso , Terry Payne

Large language models (LLMs) have been extensively studied for their abilities to generate convincing natural language sequences, however their utility for quantitative information retrieval is less well understood. Here we explore the…

Artificial intelligence (AI) is transforming society, making it crucial to prepare the next generation through AI literacy in K-12 education. However, scalable and reliable AI literacy materials and assessment resources are lacking. To…

Human-Computer Interaction · Computer Science 2024-12-03 Jiayi Wang , Ruiwei Xiao , Ying-Jui Tseng

While Large Language Models (LLMs) achieve near-human performance on standard benchmarks, their capabilities often fail to generalize to complex, real-world problems. To bridge this gap, we introduce DeepQuestion, a scalable, automated…

Computation and Language · Computer Science 2026-03-02 Ali Khoramfar , Ali Ramezani , Mohammad Mahdi Mohajeri , Mohammad Javad Dousti , Majid Nili Ahmadabadi , Heshaam Faili

Large language models (LLMs), such as ChatGPT, are able to generate human-like, fluent responses for many downstream tasks, e.g., task-oriented dialog and question answering. However, applying LLMs to real-world, mission-critical…

Computation and Language · Computer Science 2023-03-10 Baolin Peng , Michel Galley , Pengcheng He , Hao Cheng , Yujia Xie , Yu Hu , Qiuyuan Huang , Lars Liden , Zhou Yu , Weizhu Chen , Jianfeng Gao

Explainable fake news detection predicts the authenticity of news items with annotated explanations. Today, Large Language Models (LLMs) are known for their powerful natural language understanding and explanation generation abilities.…

Computation and Language · Computer Science 2024-12-25 Yifeng Wang , Zhouhong Gu , Siwei Zhang , Suhang Zheng , Tao Wang , Tianyu Li , Hongwei Feng , Yanghua Xiao

Within the evolving landscape of deep learning, the dilemma of data quantity and quality has been a long-standing problem. The recent advent of Large Language Models (LLMs) offers a data-centric solution to alleviate the limitations of…

Computation and Language · Computer Science 2024-06-24 Lin Long , Rui Wang , Ruixuan Xiao , Junbo Zhao , Xiao Ding , Gang Chen , Haobo Wang

The advent of generative Large Language Models (LLMs) such as ChatGPT has catalyzed transformative advancements across multiple domains. However, alongside these advancements, they have also introduced potential threats. One critical…

Computation and Language · Computer Science 2023-09-28 Bohan Jiang , Zhen Tan , Ayushi Nirmal , Huan Liu

Automated disinformation generation is often listed as an important risk associated with large language models (LLMs). The theoretical ability to flood the information space with disinformation content might have dramatic consequences for…

Computation and Language · Computer Science 2025-06-13 Ivan Vykopal , Matúš Pikuliak , Ivan Srba , Robert Moro , Dominik Macko , Maria Bielikova

We assess the ability of large language models (LLMs) to answer causal questions by analyzing their strengths and weaknesses against three types of causal question. We believe that current LLMs can answer causal questions with existing…

Large Language Models (LLMs) are versatile, yet they often falter in tasks requiring deep and reliable reasoning due to issues like hallucinations, limiting their applicability in critical scenarios. This paper introduces a rigorously…

Computation and Language · Computer Science 2023-11-21 Saizhuo Wang , Zhihan Liu , Zhaoran Wang , Jian Guo

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…

Software Engineering · Computer Science 2025-04-03 Nam Huynh , Beiyu Lin

This study investigates the application effectiveness of the Large Language Model (LLMs) ChatGLM in the automated generation of high school information technology exam questions. Through meticulously designed prompt engineering strategies,…

Computers and Society · Computer Science 2024-08-22 Yanxin Chen , Ling He

Multiple-choice questions (MCQs) are ubiquitous in almost all levels of education since they are easy to administer, grade, and are a reliable format in assessments and practices. One of the most important aspects of MCQs is the…

Computation and Language · Computer Science 2024-04-19 Wanyong Feng , Jaewook Lee , Hunter McNichols , Alexander Scarlatos , Digory Smith , Simon Woodhead , Nancy Otero Ornelas , Andrew Lan

The increasing prevalence of online misinformation has heightened the demand for automated fact-checking solutions. Large Language Models (LLMs) have emerged as potential tools for assisting in this task, but their effectiveness remains…

Computers and Society · Computer Science 2025-03-10 Nicolo' Fontana , Francesco Corso , Enrico Zuccolotto , Francesco Pierri

Large Language Models (LLMs) have demonstrated a powerful ability for text generation. However, achieving optimal results with a given prompt or instruction can be challenging, especially for billion-sized models. Additionally, undesired…

Computation and Language · Computer Science 2024-10-07 Lifu Tu , Semih Yavuz , Jin Qu , Jiacheng Xu , Rui Meng , Caiming Xiong , Yingbo Zhou

Automatic question generation is an important technique that can improve the training of question answering, help chatbots to start or continue a conversation with humans, and provide assessment materials for educational purposes. Existing…

Computation and Language · Computer Science 2019-02-28 Bang Liu , Mingjun Zhao , Di Niu , Kunfeng Lai , Yancheng He , Haojie Wei , Yu Xu

Large Language Models (LLMs) are transforming scientific hypothesis generation and validation by enabling information synthesis, latent relationship discovery, and reasoning augmentation. This survey provides a structured overview of…

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