tangxyw/RecSysPapers resource
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search. observed · 2026-08-28
Health v2 · maintenance only
71/100
- Activity 86
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 1478
- days_rel: n/a
- days_push: 84
- n_releases_24m: 0
Adoption not part of the score
2189 stars · 265 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A curated collection of 948+ industry and academic papers on recommendation systems, advertising, and search, organized by topics such as ranking, matching, multi-task learning, debiasing, and calibration. It is continuously updated and serves as a study and reference resource for practitioners and researchers.
Use cases
- find classic papers on recommendation systems
- study CTR prediction and ranking models
- learn about multi-task and multi-scenario modeling
- research debiasing and calibration techniques in recsys
- keep up with cutting-edge industrial recsys papers
- prepare for machine learning interviews in ads or search
When to choose
- you need a comprehensive, categorized reading list for recommendation/advertising/search research
- you want to track industry classics and frontier papers in one place
When to avoid
- you need runnable code implementations rather than papers
- you need papers outside recommendation, advertising, or search domains
Facets
learning-resource · maturity active
machine-learning search-engine developer-tools machine-learning artificial-intelligence tutorials awesome-lists cross-platform recommendation-systems papers advertising search ctr-prediction reading-list curated-collection
2 sources
- readme: https://github.com/tangxyw/RecSysPapers · fetched 2026-08-28 · 829ca308a1a5
- homepage: https://tangxyw.github.io/ · fetched 2026-08-29 · 87562e8c1587
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| tangxyw/RecSysPapers | main | 71 |
For agents
markdown · JSON · MCP: product_card(name="tangxyw/RecSysPapers")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem