tangxyw/RecSysPapers
A paper collection aggregating 946 research papers on recommendation system algorithms and techniques.
Not currently ranked — collecting fresh signals.
star history
This repository aggregates industry classics and cutting-edge research papers in recommendation, advertising, and search systems. It covers topics across the full ranking pipeline including recall, pre-rank, ranking, and re-ranking, as well as advanced techniques such as multi-task learning, multi-modal modeling, reinforcement learning, causal inference, and debiasing. Papers are organized by topic and marked with metadata including publication year, institution, and model names.
Frequently asked
- What is tangxyw/RecSysPapers?
- A paper collection aggregating 946 research papers on recommendation system algorithms and techniques.
- Is RecSysPapers open source?
- Yes — tangxyw/RecSysPapers is open source, released under the BSD-2-Clause license.
- What language is RecSysPapers written in?
- tangxyw/RecSysPapers is primarily written in Python.
- How popular is RecSysPapers?
- tangxyw/RecSysPapers has 2.2k stars on GitHub.
- Where can I find RecSysPapers?
- tangxyw/RecSysPapers is on GitHub at https://github.com/tangxyw/RecSysPapers.