Papers with clean model
Self-Supervised Learning for Contextualized Extractive Summarization (P19-1)
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| Challenge: | Existing models for extractive summarization are usually trained from scratch with a cross-entropy loss . previous work builds an end-to-end system to learn to choose sentences without explicitly modeling document context . |
| Approach: | They propose three auxiliary pre-training tasks that learn to capture the document context in a self-supervised fashion. |
| Outcome: | The proposed models outperform existing models on a CNN/DM dataset. |
PKAD: Pretrained Knowledge is All You Need to Detect and Mitigate Textual Backdoor Attacks (2024.findings-emnlp)
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| Challenge: | Current defense methods can be classified into inference-time and training-time ones based on their execution phase. |
| Approach: | They propose a two-stage poison detection strategy using pre-trained language models to detect poisoned samples before model training. |
| Outcome: | The proposed method achieves better performance than current methods more quickly and with fewer training costs. |