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Generative AI has made significant strides, yet concerns about the accuracy and reliability of its outputs continue to grow. Such inaccuracies can have serious consequences such as inaccurate decision-making, the spread of false…

Databases · Computer Science 2023-10-12 Nan Tang , Chenyu Yang , Ju Fan , Lei Cao , Yuyu Luo , Alon Halevy

Current publicly available knowledge work data collections lack diversity, extensive annotations, and contextual information about the users and their documents. These issues hinder objective and comparable data-driven evaluations and…

Artificial Intelligence · Computer Science 2024-10-25 Desiree Heim , Christian Jilek , Adrian Ulges , Andreas Dengel

In this work, we focus on the problem of distinguishing a human written news article from a news article that is created by manipulating entities in a human written news article (e.g., replacing entities with factually incorrect entities).…

Computation and Language · Computer Science 2022-03-22 Ganesh Jawahar , Muhammad Abdul-Mageed , Laks V. S. Lakshmanan

Fake news detection is a critical yet challenging problem in Natural Language Processing (NLP). The rapid rise of social networking platforms has not only yielded a vast increase in information accessibility but has also accelerated the…

Computation and Language · Computer Science 2020-07-09 Ray Oshikawa , Jing Qian , William Yang Wang

Large Language Models (LLMs) have revolutionized the domain of natural language processing (NLP) with remarkable capabilities of generating human-like text responses. However, despite these advancements, several works in the existing…

Computation and Language · Computer Science 2023-10-25 Soumya Suvra Ghosal , Souradip Chakraborty , Jonas Geiping , Furong Huang , Dinesh Manocha , Amrit Singh Bedi

Natural Language Generation (NLG) has made great progress in recent years due to the development of deep learning techniques such as pre-trained language models. This advancement has resulted in more fluent, coherent and even properties…

Computation and Language · Computer Science 2022-03-11 Wei Li , Wenhao Wu , Moye Chen , Jiachen Liu , Xinyan Xiao , Hua Wu

Previous studies have relied on existing question-answering benchmarks to evaluate the knowledge stored in large language models (LLMs). However, this approach has limitations regarding factual knowledge coverage, as it mostly focuses on…

Computation and Language · Computer Science 2023-10-31 Linhao Luo , Thuy-Trang Vu , Dinh Phung , Gholamreza Haffari

Generative AI tools are increasingly embedded in everyday work and learning, yet their fluency, opacity, and propensity to hallucinate mean that users must critically evaluate AI outputs rather than accept them at face value. The present…

Artificial Intelligence · Computer Science 2026-05-27 Gabriel R. Lau , Wei Yan Low , Louis Tay , Ysabel Guevarra , Dragan Gašević , Andree Hartanto

The advent of instruction-tuned language models that convincingly mimic human writing poses a significant risk of abuse. However, such abuse may be counteracted with the ability to detect whether a piece of text was composed by a language…

Computation and Language · Computer Science 2024-05-09 Rafael Rivera Soto , Kailin Koch , Aleem Khan , Barry Chen , Marcus Bishop , Nicholas Andrews

Generative Artificial Intelligence (GenAI) tools for source code generation have significantly boosted productivity in software development. However, they also raise concerns, particularly the risk that developers may rely heavily on these…

Software Engineering · Computer Science 2025-07-14 Otávio Cury , Guilherme Avelino

Large Language Models (LLMs) succeed in many natural language processing tasks. However, their tendency to hallucinate - generate plausible but inconsistent or factually incorrect text - can cause significant problems in certain tasks,…

Computation and Language · Computer Science 2025-08-08 Xiangyan Chen , Yujian Gan , Yimeng Gu , Matthew Purver

The propensity of Large Language Models (LLMs) to generate hallucinations and non-factual content undermines their reliability in high-stakes domains, where rigorous control over Type I errors (the conditional probability of incorrectly…

Computation and Language · Computer Science 2024-11-08 Fan Nie , Xiaotian Hou , Shuhang Lin , James Zou , Huaxiu Yao , Linjun Zhang

Although large conversational AI models such as OpenAI's ChatGPT have demonstrated great potential, we question whether such models can guarantee factual accuracy. Recently, technology companies such as Microsoft and Google have announced…

Computation and Language · Computer Science 2023-04-24 Ruochen Zhao , Xingxuan Li , Yew Ken Chia , Bosheng Ding , Lidong Bing

The Large Language Models (LLMs) exhibit remarkable ability to generate fluent content across a wide spectrum of user queries. However, this capability has raised concerns regarding misinformation and personal information leakage. In this…

Creating high-quality and realistic images is now possible thanks to the impressive advancements in image generation. A description in natural language of your desired output is all you need to obtain breathtaking results. However, as the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-15 Giuseppe Cartella , Vittorio Cuculo , Marcella Cornia , Rita Cucchiara

Video captioning aims to describe events in a video with natural language. In recent years, many works have focused on improving captioning models' performance. However, like other text generation tasks, it risks introducing factual errors…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Hui Liu , Xiaojun Wan

ChatGPT is a natural language processing tool that can engage in human-like conversations and generate coherent and contextually relevant responses to various prompts. ChatGPT is capable of understanding natural text that is input by a user…

Human-Computer Interaction · Computer Science 2024-09-02 Sara Amani , Lance White , Trini Balart , Laksha Arora , Kristi J. Shryock , Kelly Brumbelow , Karan L. Watson

Generative Artificial Intelligence (GenAI) has demonstrated its capabilities in the present world that reduce human effort significantly. It utilizes deep learning techniques to create original and realistic content in terms of text,…

Artificial Intelligence · Computer Science 2025-12-11 Aman Kumar , Deepak Narayan Gadde

Natural language counterfactual generation aims to minimally modify a given text such that the modified text will be classified into a different class. The generated counterfactuals provide insight into the reasoning behind a model's…

Computation and Language · Computer Science 2024-10-08 Yongjie Wang , Xiaoqi Qiu , Yu Yue , Xu Guo , Zhiwei Zeng , Yuhong Feng , Zhiqi Shen

This survey addresses the crucial issue of factuality in Large Language Models (LLMs). As LLMs find applications across diverse domains, the reliability and accuracy of their outputs become vital. We define the Factuality Issue as the…