# PaddlePaddle/Research

novel deep learning research works with PaddlePaddle

Repository: https://github.com/PaddlePaddle/Research
Canonical: https://ross.abutalabs.com/products/paddlepaddle-research
Language: Python
License: Apache-2.0
License Family: permissive
Topics: deep-learning, computer-vision, nlp, knowledge-graph, spatial-temporal, data-mining
Last push: 2024-08-16T02:42:22+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2393, "days_push": 747, "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 1763, forks 768 (observed 2026-08-28T04:05:32.856886+00:00)

## What it is
A collection of novel deep learning research works implemented with PaddlePaddle, covering top-conference papers and competition-winning models in computer vision, NLP, knowledge graphs, and spatial-temporal data mining. Each subdirectory provides reproducible code for a specific paper or competition solution.

## Use cases
- reproduce deep learning research papers in paddlepaddle
- find competition-winning computer vision models
- implement vehicle re-identification
- build chinese nlp models like lexical analysis and dialogue matching
- learn few-shot learning baselines
- semantic segmentation on cityscapes and ade20k
- text-to-sql semantic parsing baseline

## When to choose
- you use PaddlePaddle and want reference implementations of published research
- you need proven competition solutions for CV or NLP tasks
- you want to study top-conference paper code in Chinese NLP or knowledge graphs

## When to avoid
- you work exclusively in PyTorch or TensorFlow
- you need a production-ready maintained library rather than research code
- you need a single coherent API - this is a loose collection of independent projects

## Facets
- artifact type: learning-resource
- maturity: active
- function: deep-learning, machine-learning, nlp, computer-vision, image-processing
- domain: deep-learning, computer-vision, data-science
- platform: python
- tags: paddlepaddle, research-papers, competition-solutions, knowledge-graph, spatial-temporal-data-mining, model-zoo, natural-language-processing, gpu

## Member repositories
- PaddlePaddle/Research (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:32.856886+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 2026-08-30T03:26:45.104331+00:00, confidence not recorded.
  - readme: https://github.com/PaddlePaddle/Research (fetched 2026-08-28T04:05:32.856886+00:00, sha cb2163dfdf3c)
- Data as of 2026-08-30T08:39:29.467469+00:00.