Papers by Jingzhao Zhang
Exposure Bias versus Self-Recovery: Are Distortions Really Incremental for Autoregressive Text Generation? (2021.emnlp-main)
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| Challenge: | Exposure bias is a central problem for auto-regressive language models (LM) it is believed that teacher forcing would cause test-time generation to be incrementally distorted due to the training-generation discrepancy. |
| Approach: | They propose to quantify the impact of exposure bias in quality, diversity, consistency and consistency by using ground-truth data prefixes instead of prefix generated by the model. |
| Outcome: | The proposed model performs better when the training-generation discrepancy is removed . the model is more robust and self-recovery ability is shown to counter exposure bias. |