Papers with Two-pass model
TAPIR: Learning Adaptive Revision for Incremental Natural Language Understanding with a Two-Pass Model (2023.findings-acl)
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| Challenge: | Recent approaches for incremental processing use RNNs or Transformers, which consume whole sequences and are by nature non-incremental. |
| Approach: | They propose a two-pass model for AdaPtIve Revision to obtain an incremental supervision signal for learning an adaptive revision policy. |
| Outcome: | The proposed model has better incremental performance and faster inference speed compared to restart-incremental Transformers while showing little degradation on full sequences. |