News Classification
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Benchmarks
N15News
Most implemented
Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
LUX (Linguistic aspects Under eXamination): Discourse Analysis for Automatic Fake News Classification
Accuracy of TextFooler black box adversarial attacks on 01 loss sign activation neural network ensemble
A Novel Perspective to Look At Attention: Bi-level Attention-based Explainable Topic Modeling for News Classification
Knowledge Graph informed Fake News Classification via Heterogeneous Representation Ensembles
Tri-Learn Graph Fusion Network for Attributed Graph Clustering
Papers
DunbaaBERT: From Sacrifice to Semantics
Large language models have achieved strong performance across many NLP tasks, yet Urdu remains comparatively underexplored due to limited resources and fragmented evaluation settings. To address this gap, we introduce Du…
Linguistic AcceptabilityNews ClassificationSentiment AnalysisHybrid Feature Combinations with CNN for Bangla Fake News Classification
Nowadays, people in Bangladesh frequently rely on the internet and social media for daily news instead of traditional newspapers. However, the spread of false Bangla news through these platforms poses risks and challenge…
News ClassificationAddressing Data Scarcity in Bangla Fake News Detection: An LLM-Based Dataset Augmentation Approach
The growing spread of misinformation in digital media highlights the need for reliable fake news detection systems, yet progress in under-resourced languages such as Bangla is limited by small and imbalanced datasets. Th…
Fake News DetectionNews ClassificationMultiPress: A Multi-Agent Framework for Interpretable Multimodal News Classification
With the growing prevalence of multimodal news content, effective news topic classification demands models capable of jointly understanding and reasoning over heterogeneous data such as text and images. Existing methods …
News ClassificationMzansiText and MzansiLM: An Open Corpus and Decoder-Only Language Model for South African Languages
Decoder-only language models can be adapted to diverse tasks through instruction finetuning, but the extent to which this generalizes at small scale for low-resource languages remains unclear. We focus on the languages o…
Natural Language UnderstandingData-to-Text GenerationNews ClassificationLeft, Right, or Center? Evaluating LLM Framing in News Classification and Generation
Large Language Model (LLM) based summarization and text generation are increasingly used for producing and rewriting text, raising concerns about political framing in journalism where subtle wording choices can shape int…
News ClassificationText Generation