News Classification
24 papers with code • 3 benchmarks • 11 datasets
Benchmarks
These leaderboards are used to track progress in News Classification
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Datasets
IndicGLUE
N15News
CIDII Dataset
Most implemented papers
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
The proliferation of fake news, i. e., news intentionally spread for misinformation, poses a threat to individuals and society.
AraCOVID19-MFH: Arabic COVID-19 Multi-label Fake News and Hate Speech Detection Dataset
This paper releases "AraCOVID19-MFH" a manually annotated multi-label Arabic COVID-19 fake news and hate speech detection dataset.
Knowledge Graph informed Fake News Classification via Heterogeneous Representation Ensembles
bkolosk1/kbnr
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Increasing amounts of freely available data both in textual and relational form offers exploration of richer document representations, potentially improving the model performance and robustness.
A Novel Perspective to Look At Attention: Bi-level Attention-based Explainable Topic Modeling for News Classification
ruixinhua/batm
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Findings (ACL) 2022
Many recent deep learning-based solutions have widely adopted the attention-based mechanism in various tasks of the NLP discipline.
Speed Reading: Learning to Read ForBackward via Shuttle
tsujuifu/pytorch_lstm-shuttle
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EMNLP 2018
We present LSTM-Shuttle, which applies human speed reading techniques to natural language processing tasks for accurate and efficient comprehension.
Fake News Detection as Natural Language Inference
The remainder of test cases are classified by our ensemble.
Do Sentence Interactions Matter? Leveraging Sentence Level Representations for Fake News Classification
MysteryVaibhav/fake_news_semantics
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WS 2019
The rising growth of fake news and misleading information through online media outlets demands an automatic method for detecting such news articles.
Assessing Robustness of Text Classification through Maximal Safe Radius Computation
EmanueleLM/MCTS
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Findings of the Association for Computational Linguistics 2020
Neural network NLP models are vulnerable to small modifications of the input that maintain the original meaning but result in a different prediction.
KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi
Andrews2017/KINNEWS-and-KIRNEWS-Corpus
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COLING 2020
Recent progress in text classification has been focused on high-resource languages such as English and Chinese.
IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages
AI4Bharat/indic-bert
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Findings of the Association for Computational Linguistics 2020
These resources include: (a) large-scale sentence-level monolingual corpora, (b) pre-trained word embeddings, (c) pre-trained language models, and (d) multiple NLU evaluation datasets (IndicGLUE benchmark).
