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
Information Retrieval models present us different ways for probabilistic modeling of documents and q...
Abstract: Document Retrieval is the computerized process of producing a relevance ranked list of doc...
Summarization is the notion of abstracting key content from information sources. The task of summari...
Large-scale retrieval is to recall relevant documents from a huge collection given a query. It relie...
Abstract. We show that several previously proposed passage-based doc-ument ranking principles, along...
Reproducability paper of the paper "BERT-PLI: Modeling Paragraph-Level Interactions for Legal Case R...
In this work I detail the compilation of a unique corpus of Norwegian court decisions. I utilize thi...
The advent of contextualised language models has brought gains in search effectiveness, not just whe...
The aims of this paper are twofold. Our first aim is to compare results of the earlier Terabyte trac...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
We observe that in curated documents the distribution of the occurrences of salient terms, e.g., ter...
Statutory article retrieval is the task of automatically retrieving law articles relevant to a legal...
Introduction Recent advances in Information Retrieval are based on using Statistical Language Model...
Document-level representation attracts more and more research attention. Recent Transformer-based pr...
In this paper, we present our approaches for the case law retrieval and the legal case entailment ta...
Information Retrieval models present us different ways for probabilistic modeling of documents and q...
Abstract: Document Retrieval is the computerized process of producing a relevance ranked list of doc...
Summarization is the notion of abstracting key content from information sources. The task of summari...
Large-scale retrieval is to recall relevant documents from a huge collection given a query. It relie...
Abstract. We show that several previously proposed passage-based doc-ument ranking principles, along...
Reproducability paper of the paper "BERT-PLI: Modeling Paragraph-Level Interactions for Legal Case R...
In this work I detail the compilation of a unique corpus of Norwegian court decisions. I utilize thi...
The advent of contextualised language models has brought gains in search effectiveness, not just whe...
The aims of this paper are twofold. Our first aim is to compare results of the earlier Terabyte trac...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
We observe that in curated documents the distribution of the occurrences of salient terms, e.g., ter...
Statutory article retrieval is the task of automatically retrieving law articles relevant to a legal...
Introduction Recent advances in Information Retrieval are based on using Statistical Language Model...
Document-level representation attracts more and more research attention. Recent Transformer-based pr...
In this paper, we present our approaches for the case law retrieval and the legal case entailment ta...
Information Retrieval models present us different ways for probabilistic modeling of documents and q...
Abstract: Document Retrieval is the computerized process of producing a relevance ranked list of doc...
Summarization is the notion of abstracting key content from information sources. The task of summari...