English
Related papers

Related papers: Preprint: Poster: Did I Just Browse A Website Writ…

200 papers

Many recent news reports have claimed that content generated by large language models (LLMs) is taking over the web. However, these claims are typically not based on a representative sample of the web and the methodology underlying them is…

Networking and Internet Architecture · Computer Science 2026-05-04 Sichang Steven He , Calvin Ardi , Ramesh Govindan , Harsha V. Madhyastha

The dissemination of Large Language Models (LLMs), trained at scale, and endowed with powerful text-generating abilities, has made it easier for all to produce harmful, toxic, faked or forged content. In response, various proposals have…

Computation and Language · Computer Science 2025-06-12 Matthieu Dubois , François Yvon , Pablo Piantanida

The powerful ability to understand, follow, and generate complex language emerging from large language models (LLMs) makes LLM-generated text flood many areas of our daily lives at an incredible speed and is widely accepted by humans. As…

Computation and Language · Computer Science 2024-04-22 Junchao Wu , Shu Yang , Runzhe Zhan , Yulin Yuan , Derek F. Wong , Lidia S. Chao

Since the proliferation of LLMs, there have been concerns about their misuse for harmful content creation and spreading. Recent studies justify such fears, providing evidence of LLM vulnerabilities and high potential of their misuse. Humans…

Computation and Language · Computer Science 2025-03-20 Dominik Macko , Robert Moro , Ivan Srba

An ideal detection system for machine generated content is supposed to work well on any generator as many more advanced LLMs come into existence day by day. Existing systems often struggle with accurately identifying AI-generated content…

The ability of large language models to generate complex texts allows them to be widely integrated into many aspects of life, and their output can quickly fill all network resources. As the impact of LLMs grows, it becomes increasingly…

Computation and Language · Computer Science 2024-11-12 Yongye Su , Yuqing Wu

Developing algorithms to differentiate between machine-generated texts and human-written texts has garnered substantial attention in recent years. Existing methods in this direction typically concern an offline setting where a dataset…

Machine Learning · Computer Science 2025-06-09 Can Chen , Jun-Kun Wang

The burgeoning capabilities of advanced large language models (LLMs) such as ChatGPT have led to an increase in synthetic content generation with implications across a variety of sectors, including media, cybersecurity, public discourse,…

Computation and Language · Computer Science 2023-10-25 Xianjun Yang , Liangming Pan , Xuandong Zhao , Haifeng Chen , Linda Petzold , William Yang Wang , Wei Cheng

Large language models (LLMs) such as GPT, Claude, Gemini, and Grok have been deeply integrated into our daily life. They now support a wide range of tasks -- from dialogue and email drafting to assisting with teaching and coding, serving as…

Computation and Language · Computer Science 2026-01-13 Hongyi Zhou , Jin Zhu , Ying Yang , Chengchun Shi

The emergence of large language models (LLMs) has resulted in the production of LLM-generated texts that is highly sophisticated and almost indistinguishable from texts written by humans. However, this has also sparked concerns about the…

Computation and Language · Computer Science 2023-06-06 Ruixiang Tang , Yu-Neng Chuang , Xia Hu

With the widespread use of large language models (LLMs), many researchers have turned their attention to detecting text generated by them. However, there is no consistent or precise definition of their target, namely "LLM-generated text".…

Computation and Language · Computer Science 2025-10-24 Mingmeng Geng , Thierry Poibeau

Verifying the provenance of content is crucial to the functioning of many organizations, e.g., educational institutions, social media platforms, and firms. This problem is becoming increasingly challenging as text generated by Large…

Machine Learning · Statistics 2026-03-24 Tara Radvand , Mojtaba Abdolmaleki , Mohamed Mostagir , Ambuj Tewari

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

As more content generated by large language models (LLMs) floods into the Internet, information retrieval (IR) systems now face the challenge of distinguishing and handling a blend of human-authored and machine-generated texts. Recent…

Information Retrieval · Computer Science 2025-08-26 Wei Huang , Keping Bi , Yinqiong Cai , Wei Chen , Jiafeng Guo , Xueqi Cheng

The growing use of large language models (LLMs) for text generation has led to widespread concerns about AI-generated content detection. However, an overlooked challenge is AI-polished text, where human-written content undergoes subtle…

Computation and Language · Computer Science 2025-05-06 Shoumik Saha , Soheil Feizi

The advent of Large Language Models (LLMs) has shown the potential to improve relevance and provide direct answers in web searches. However, challenges arise in validating the reliability of generated results and the credibility of…

Information Retrieval · Computer Science 2023-10-20 Xiang Shi , Jiawei Liu , Yinpeng Liu , Qikai Cheng , Wei Lu

The proliferation of large language models (LLMs) has significantly transformed the digital information landscape, making it increasingly challenging to distinguish between human-written and LLM-generated content. Detecting LLM-generated…

Computation and Language · Computer Science 2025-06-30 Minjia Mao , Dongjun Wei , Xiao Fang , Michael Chau

Large language models (LLMs) have achieved human-level text generation, emphasizing the need for effective AI-generated text detection to mitigate risks like the spread of fake news and plagiarism. Existing research has been constrained by…

Computation and Language · Computer Science 2024-05-22 Yafu Li , Qintong Li , Leyang Cui , Wei Bi , Zhilin Wang , Longyue Wang , Linyi Yang , Shuming Shi , Yue Zhang

Exploring the data sources used to train Large Language Models (LLMs) is a crucial direction in investigating potential copyright infringement by these models. While this approach can identify the possible use of copyrighted materials in…

Computation and Language · Computer Science 2024-09-24 Weijie Zhao , Huajie Shao , Zhaozhuo Xu , Suzhen Duan , Denghui Zhang

With the emergence of widely available powerful LLMs, disinformation generated by large Language Models (LLMs) has become a major concern. Historically, LLM detectors have been touted as a solution, but their effectiveness in the real world…

Computation and Language · Computer Science 2024-09-30 Henrique Da Silva Gameiro , Andrei Kucharavy , Ljiljana Dolamic
‹ Prev 1 2 3 10 Next ›