Search Results for author:
Found 5 papers, 2 papers with code
ALISON: Fast and Effective Stylometric Authorship Obfuscation
AO is the corresponding adversarial task, aiming to modify a text in such a way that its semantics are preserved, yet an AA model cannot correctly infer its authorship.
A Ship of Theseus: Curious Cases of Paraphrasing in LLM-Generated Texts
In the realm of text manipulation and linguistic transformation, the question of authorship has always been a subject of fascination and philosophical inquiry.
The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis
We conduct an inquiry into the sociotechnical aspects of sentiment analysis (SA) by critically examining 189 peer-reviewed papers on their applications, models, and datasets.
GPT-who: An Information Density-based Machine-Generated Text Detector
We examine if this UID principle can help capture differences between Large Language Models (LLMs)-generated and human-generated texts.
How do decoding algorithms distribute information in dialogue responses?
We find that (i) surprisingly, model-generated responses follow the UID principle to a greater extent than human responses, and (ii) decoding algorithms that promote UID do not generate higher-quality responses.
