Search Results for author:
Found 6 papers, 3 papers with code
Learning Universal Authorship Representations
Determining whether two documents were composed by the same author, also known as authorship verification, has traditionally been tackled using statistical methods.
AdapterSwap: Continuous Training of LLMs with Data Removal and Access-Control Guarantees
Large language models (LLMs) are increasingly capable of completing knowledge intensive tasks by recalling information from a static pretraining corpus.
Few-Shot Detection of Machine-Generated Text using Style Representations
Furthermore, given a handful of examples composed by each of several specific language models of interest, our approach affords the ability to predict which model generated a given document.
Learning to Generate Text in Arbitrary Writing Styles
However, in applications such as writing assistants, it is desirable for language models to produce text in an author-specific style on the basis of a potentially small writing sample.
Defending Against Disinformation Attacks in Open-Domain Question Answering
Recent work in open-domain question answering (ODQA) has shown that adversarial poisoning of the search collection can cause large drops in accuracy for production systems.
A Deep Metric Learning Approach to Account Linking
We consider the task of linking social media accounts that belong to the same author in an automated fashion on the basis of the content and metadata of their corresponding document streams.
