all AI news
From Text to Source: Results in Detecting Large Language Model-Generated Content
March 28, 2024, 4:48 a.m. | Wissam Antoun, Beno\^it Sagot, Djam\'e Seddah
cs.CL updates on arXiv.org arxiv.org
Abstract: The widespread use of Large Language Models (LLMs), celebrated for their ability to generate human-like text, has raised concerns about misinformation and ethical implications. Addressing these concerns necessitates the development of robust methods to detect and attribute text generated by LLMs. This paper investigates "Cross-Model Detection," by evaluating whether a classifier trained to distinguish between source LLM-generated and human-written text can also detect text from a target LLM without further training. The study comprehensively explores …
abstract arxiv concerns cs.cl development ethical ethical implications generate generated human human-like language language model language models large language large language model large language models llms misinformation paper results robust text type
More from arxiv.org / cs.CL updates on arXiv.org
Jobs in AI, ML, Big Data
Senior Machine Learning Engineer
@ GPTZero | Toronto, Canada
Customer Data Analyst with Spanish
@ Michelin | Voluntari
HC Data Analyst - Senior
@ Leidos | 1662 Intelligence Community Campus - Bethesda MD
Healthcare Research & Data Analyst- Infectious, Niche, Rare Disease
@ Clarivate | Remote (121- Massachusetts)
Data Analyst (maternity leave cover)
@ Clarivate | R155-Belgrade
Sales Enablement Data Analyst (Remote)
@ CrowdStrike | USA TX Remote