Published December 14, 2021
| Version v1
Conference paper
Open
PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval
Description
Here the models described in the publication "PARM: A Paragraph Aggregation Retrieval Model for Dense Document-to-Document Retrieval" are uploaded. The models are the DPR models denoted as LegalBERT_doc and LegalBERT_para in the paper.
The dense retriever models can be loaded with the DPR libary from Facebook Research (https://github.com/facebookresearch/DPR).
LegalBERT_para is the dense passage retrieval encoder based on LegalBERT and trained on the paragraph-level labels of COLIEE Task 2 data.
LegalBERT_doc is the dense passage retrieval encoder based on LegalBERT and trained on the paragraph-level and document-level labels of COLIEE Task 1&2 data.
Files
legal_bert_doc.zip
Files
(4.4 GB)
| Name | Size | Download all |
|---|---|---|
|
md5:2c77a272272acb0a3ecda5bfe2cc5532
|
2.2 GB | Preview Download |
|
md5:3b23f71d2d649d32c48305629198e08b
|
2.1 GB | Preview Download |