Search Results for author:
Found 2 papers, 0 papers with code
Autoregressive Entity Generation for End-to-End Task-Oriented Dialog
In either approach, the systems may generate a response with conflicting entity information.
Bi-Granularity Contrastive Learning for Post-Training in Few-Shot Scene
The major paradigm of applying a pre-trained language model to downstream tasks is to fine-tune it on labeled task data, which often suffers instability and low performance when the labeled examples are scarce.~One way to alleviate this problem is to apply post-training on unlabeled task data before fine-tuning, adapting the pre-trained model to target domains by contrastive learning that considers either token-level or sequence-level similarity.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
