Papers with learning bias
Mitigating the Learning Bias towards Repetition by Self-Contrastive Training for Open-Ended Generation (2023.findings-acl)
Copied to clipboard
| Challenge: | Existing language models generate repetitive texts with greedy decoding or beam search. |
| Approach: | They propose a self-contrastive training technique to penalize the output of a premature checkpoint of the same model when it incorrectly predicts repetition. |
| Outcome: | The proposed training mitigates repetition while maintaining fluency while minimizing the overestimation of token-level repetition probabilities. |
Task-Aware Self-Supervised Framework for Dialogue Discourse Parsing (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing discourse parsing approaches are constrained by predefined relation types, which can impede the adaptability of the parser for downstream tasks. |
| Approach: | They propose to introduce a task-aware paradigm to improve the versatility of the parser. |
| Outcome: | Empirical studies on dialogue discourse parsing datasets and a downstream task demonstrate the proposed framework. |