摘要大数据(Big Data) 已成为学术界和产业界的研究热点, 正影响着人们日常生活,
工作习惯及思考方式. 但是目前大数据在收集, 存储和使用过程中面临着诸多安全风险 …

Potential harms of large language models can be mitigated by watermarking model output,
ie, embedding signals into generated text that are invisible to humans but algorithmically …

Recent advances in the capabilities of large language models such as GPT-4 have spurred
increasing concern about our ability to detect AI-generated text. Prior works have suggested …

During the recent years, the issue of preserving the integrity of digital text has become a
focus of interest in the transmission of online content on the Internet. Watermarking has a …

The past 3 years of work in NLP have been characterized by the development and
deployment of ever larger language models, especially for English. BERT, its variants, GPT …

Nowadays, big data has become ubiquitous. Big data contains great value and chance.
However, big data also brings many security risks and privacy-preserving problems. Security …

As AI-generated text increasingly resembles human-written content, the ability to detect
machine-generated text becomes crucial. To address this challenge, we present …

Recent years have witnessed a proliferation of valuable original natural language contents
found in subscription-based media outlets, web novel platforms, and outputs of large …

Watermarking generative models consists of planting a statistical signal (watermark) in a
model's output so that it can be later verified that the output was generated by the given …

With the remarkable generation performance of large language models, ethical and legal
concerns about using them have been raised, such as plagiarism and copyright issues. For …