A Survey on Fake Review Detection: From Pre-trained Language Models to Large Language Models
cs.CL, cs.AI
Submitted: 2026-09-12
Updated: 2026-09-12
Terminology
Sources
- Large Language Models as 'Hidden Persuaders': Fake Product Reviews are Indistinguishable to Humans and Machines
- ScoreGAN: A Fraud Review Detector based on Multi Task Learning of Regulated GAN with Data Augmentation
- Towards Accurate Deceptive Opinion Spam Detection based on Word Order-preserving CNN
- Data Augmentation for Fake Reviews Detection in Multiple Languages and Multiple Domains
- What Matters in Explanations: Towards Explainable Fake Review Detection Focusing on Transformers
- Hidden in Plain Sight: Evaluation of the Deception Detection Capabilities of LLMs in Multimodal Settings
- Fake Reviews Detection through Analysis of Linguistic Features
- MAiDE-up: Multilingual Deception Detection of GPT-generated Hotel Reviews
- Detecting LLM-Generated Spam Reviews by Integrating Language Model Embeddings and Graph Neural Network
- Is ChatGPT a General-Purpose Natural Language Processing Task Solver?
- Finding Deceptive Opinion Spam by Any Stretch of the Imagination
- RoBERTa: A Robustly Optimized BERT Pretraining Approach
- Efficient Estimation of Word Representations in Vector Space
- Deep contextualized word representations
- ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
- DeBERTa: Decoding-enhanced BERT with Disentangled Attention
- ERNIE: Enhanced Representation through Knowledge Integration
- An Overview of Multi-Task Learning in Deep Neural Networks
- Don't Stop Pretraining: Adapt Language Models to Domains and Tasks
- How to Fine-Tune BERT for Text Classification?
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