# icoxfog417/awesome-text-summarization

The guide to tackle with the Text Summarization

Repository: https://github.com/icoxfog417/awesome-text-summarization
Canonical: https://ross.abutalabs.com/products/awesome-text-summarization
License: MIT
License Family: permissive
Topics: text-summarization, machine-learning, python, natural-language-processing
Last push: 2022-11-27T16:08:01+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3256, "days_push": 1375, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1311, forks 203 (observed 2026-08-28T04:04:20.046188+00:00)

## What it is
A curated awesome-list guide to text summarization, covering task definitions, extractive and abstractive approaches, transfer learning, evaluation, and links to datasets, libraries, papers, and articles. It is an educational reference rather than runnable software.

## Use cases
- learn about text summarization techniques
- find datasets for summarization research
- compare extractive vs abstractive summarization methods
- find python libraries for document summarization
- understand how to evaluate summarization models
- find papers on neural text summarization

## When to choose
- you are starting to learn text summarization and want a curated overview
- you need pointers to datasets, libraries, and papers in one place

## When to avoid
- you need a ready-to-use summarization model or library
- you need actively maintained code rather than a reference list

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: nlp, machine-learning
- domain: machine-learning, tutorials
- platform: python
- tags: awesome-list, text-summarization, extractive-summarization, abstractive-summarization, curated-resources, natural-language-processing

## Member repositories
- icoxfog417/awesome-text-summarization (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:20.046188+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:49:50.104637+00:00, confidence not recorded.
  - readme: https://github.com/icoxfog417/awesome-text-summarization (fetched 2026-08-28T04:04:20.046188+00:00, sha 1d405fb6ba29)
- Data as of 2026-08-30T08:39:29.467469+00:00.