mlsanityData to 7 Oct 2026

JNLP Team: Deep Learning Approaches for Legal Processing Tasks in COLIEE 2021

arXiv 2106.13405 ↗First posted 25 Jun 2021cs.CLcited by 8

Not on the map. Why?

Abstract (arXiv)

COLIEE is an annual competition in automatic computerized legal text processing. Automatic legal document processing is an ambitious goal, and the structure and semantics of the law are often far more complex than everyday language. In this article, we survey and report our methods and experimental results in using deep learning in legal document processing. The results show the difficulties as well as potentials in this family of approaches.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 6 of its 13 references that are in the map. First posted on arXiv 25 Jun 2021.

Builds on

6 of 13 references.

References · 6

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  3. 2020Building Legal Case Retrieval Systems with Lexical Matching and Summarization using A Pre-Trained Phrase Scoring Modelcited by 24
  4. 2020JNLP Team: Deep Learning for Legal Processing in COLIEE 2020cited by 14
  5. 2021IITP@COLIEE 2019: Legal Information Retrieval using BM25 and BERTcited by 5
  6. 2019Threshold-Based Retrieval and Textual Entailment Detection on Legal Bar Exam Questionscited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 1; 2023: 3; 2024: 1; 2025: 1; 2026: 1.

8 papers.