Pith. sign in

REVIEW 1 cited by

HADES: Homologous Automated Document Exploration and Summarization

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2302.13099 v1 pith:22GQWCHY submitted 2023-02-25 cs.CL

classification cs.CL
keywords documentshadesanalysiscomparativedealingdocumentprofessionalssummarization
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

This paper introduces HADES, a novel tool for automatic comparative documents with similar structures. HADES is designed to streamline the work of professionals dealing with large volumes of documents, such as policy documents, legal acts, and scientific papers. The tool employs a multi-step pipeline that begins with processing PDF documents using topic modeling, summarization, and analysis of the most important words for each topic. The process concludes with an interactive web app with visualizations that facilitate the comparison of the documents. HADES has the potential to significantly improve the productivity of professionals dealing with high volumes of documents, reducing the time and effort required to complete tasks related to comparative document analysis. Our package is publically available on GitHub.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Legal Document Summarization: Enhancing Judicial Efficiency through Automation Detection

    cs.CL 2025-07 reject novelty 1.0 of 10

    A legal document summarization framework is described, but the experiments use four non-legal summarization datasets and generic equations, so the claimed judicial efficiency improvements are not established.

Pith tools