Search Results for author:
Found 2 papers, 1 papers with code
Financial Report Chunking for Effective Retrieval Augmented Generation
We introduce a novel framework that evaluates how chunking based on element types annotated by document understanding models contributes to the overall context and accuracy of the information retrieved.
BabyBear: Cheap inference triage for expensive language models
For named entity recognition, we save 33% of the deep learning compute while maintaining an F1 score higher than 95% on the CoNLL benchmark.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
