# wzhe06/Reco-papers

Classic papers and resources on recommendation

Repository: https://github.com/wzhe06/Reco-papers
Canonical: https://ross.abutalabs.com/products/reco-papers
Homepage: https://github.com/wzhe06/Reco-papers
Language: Python
License: MIT
License Family: permissive
Topics: recommender-system, deep-learning, machine-learning, recommendation, exploration-exploitation, reinforcement-learning
Last push: 2025-10-16T18:11:27+00:00

## Health v2 (maintenance only)
Score: 53/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 47, release rhythm 35, longevity 100
- inputs: {"age_days": 3018, "days_push": 321, "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 3570, forks 813 (observed 2026-08-28T04:08:10.087080+00:00)

## What it is
A curated, continuously updated collection of classic and industry papers, learning materials, and talks on recommender systems, organized by topic such as retrieval and rerank, embeddings, cold start, and LLM-based recommendation. It serves as a study and reference resource rather than runnable software.

## Use cases
- find classic recommender system papers
- learn deep learning recommendation models
- study retrieval and reranking techniques
- research LLM-based recommendation
- prepare for machine learning interviews on recsys
- find industry practice articles on recommendation systems

## When to choose
- you want a curated, topic-organized reading list for recommender systems
- you need industry papers on ranking, embeddings, and exploration-exploitation
- you are studying or teaching recommendation algorithms

## When to avoid
- you need runnable recommendation code or a library
- you want a maintained software tool rather than papers and resources

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, rag, search-engine
- domain: machine-learning, tutorials, awesome-lists, data-science
- platform: cross-platform
- tags: recommender-system, papers, curated-list, deep-learning, reinforcement-learning, llm

## Member repositories
- wzhe06/Reco-papers (main) score 53

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:10.087080+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 2026-08-29T18:34:07.734665+00:00, confidence not recorded.
  - readme: https://github.com/wzhe06/Reco-papers (fetched 2026-08-28T04:08:10.087080+00:00, sha 1716014b3249)
  - homepage: https://github.com/wzhe06/Reco-papers (fetched 2026-08-29T09:27:40.842734+00:00, sha 636f421ce1bb)
- Data as of 2026-08-30T08:39:29.467469+00:00.