Improving language models fine-tuning with representation consistency targets

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Progressive Prompts: Continual Learning for Language Models (2023, background): “Regularization-based approaches are more memoryefficient than replay-based approaches, but suffer from catastrophic forgetting and are often not suitable for long task sequences (Kirkpatrick et al., 2017; Razdaibiedina et al., 2022).”