FactLLaMA: Optimizing Instruction-Following Language Models with External Knowledge for Automated Fact-Checking

Author:

Cheung Tsun-Hin1,Lam Kin-Man1

Affiliation:

1. The Hong Kong Polytechnic University,Department of Electrical and Electronic Engineering,Kowloon, Hong Kong

Publisher

IEEE

Reference27 articles.

1. Attention is all you need;vaswani;Advances in neural information processing systems,2017

2. DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning

3. Knowledge Enhanced Fact Checking and Verification

4. BERT: Pre-training of deep bidirectional transformers for language understanding;devlin;NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics Human Language Technologies - Proceedings of the Conference,2019

5. Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking

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1. Combating misinformation in the age of LLMs: Opportunities and challenges;AI Magazine;2024-08

2. Sentiment score-based classification for fake news using machine learning and LSTM-BiLSTM;Soft Computing;2024-07-24

3. Preventing and Detecting Misinformation Generated by Large Language Models;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

4. An In-depth Analysis of Transformer Models for Enhanced Performance in Fake News Detection;2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN);2024-07-03

5. Enhanced detection of fabricated news through sentiment analysis and text feature extraction;International Journal of Information Technology;2024-06-08

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