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Found 5 papers, 1 papers with code
Keyword Assisted Embedded Topic Model
By illuminating latent structures in a corpus of text, topic models are an essential tool for categorizing, summarizing, and exploring large collections of documents.
Crowd-Machine Collaboration for Item Screening
In this paper we describe how crowd and machine classifier can be efficiently combined to screen items that satisfy a set of predicates.
Tweeki: Linking Named Entities on Twitter to a Knowledge Graph
Further, there is a lack of a large, linked corpus of tweets to aid researchers, along with lack of gold dataset to evaluate the accuracy of entity linking.
Noise Audits Improve Moral Foundation Classification
Morality classification relies on human annotators to label the moral expressions in text, which provides training data to achieve state-of-the-art performance.
Risk and Response in Large Language Models: Evaluating Key Threat Categories
This paper explores the pressing issue of risk assessment in Large Language Models (LLMs) as they become increasingly prevalent in various applications.
