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Bias in Opinion Summarisation from Pre-training to Adaptation: A Case Study in Political Bias
In this study, using political bias as a case study, we first establish a methodology to quantify bias in abstractive models, then trace it from the pre-trained models to the task of summarising social media opinions using different models and adaptation methods.
Examining Bias in Opinion Summarisation Through the Perspective of Opinion Diversity
We found that BART and ChatGPT can better capture diverse opinions presented in the source documents.
Knowledge Capture and Replay for Continual Learning
Deep neural networks have shown promise in several domains, and the learned data (task) specific information is implicitly stored in the network parameters.
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