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Found 8 papers, 4 papers with code
Targets and Aspects in Social Media Hate Speech
Mainstream research on hate speech focused so far predominantly on the task of classifying mainly social media posts with respect to predefined typologies of rather coarse-grained hate speech categories.
GPT-HateCheck: Can LLMs Write Better Functional Tests for Hate Speech Detection?
A recent proposal in this direction is HateCheck, a suite for testing fine-grained model functionalities on synthesized data generated using templates of the kind "You are just a [slur] to me."
Towards Weakly-Supervised Hate Speech Classification Across Datasets
As pointed out by several scholars, current research on hate speech (HS) recognition is characterized by unsystematic data creation strategies and diverging annotation schemata.
Verifying the Robustness of Automatic Credibility Assessment
Text classification methods have been widely investigated as a way to detect content of low credibility: fake news, social media bots, propaganda, etc.
Error syntax aware augmentation of feedback comment generation dataset
This paper presents a solution to the GenChal 2022 shared task dedicated to feedback comment generation for writing learning.
Multilingual Extraction and Categorization of Lexical Collocations with Graph-aware Transformers
Recognizing and categorizing lexical collocations in context is useful for language learning, dictionary compilation and downstream NLP.
Concept Extraction Using Pointer-Generator Networks
Concept extraction is crucial for a number of downstream applications.
Improving Scientific Article Visibility by Neural Title Simplification
The rapidly growing amount of data that scientific content providers should deliver to a user makes them create effective recommendation tools.
