Papers with generalization of retrieval-augmented language models

1 papers
On the Generalization Ability of Retrieval-Enhanced Transformers (2023.findings-eacl)

Copied to clipboard

Challenge: Recent work on retrieval-augmented language models has shown impressive results . performance gains from retrieval to a large extent originate from overlapping tokens between the database and test data, suggesting less of non-trivial generalization than previously assumed.
Approach: They propose to off-load memory from trainable weights to a retrieval database and compare it to larger models with a larger model.
Outcome: The proposed model outperforms GPT-3 and Jurassic-1 on the Pile at 4% of the model parameters.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations