Ask HN: What are the recommender systems papers from 2024-2025?
I’ve been keeping up with the classics (NCF, Wide & Deep, LightGCN), but the field seems to have shifted dramatically in the last 18–24 months toward LLM-based reasoning and graph-based retrieval at scale.
I’m looking for the "state of the art" in 2026. Specifically:
LLM4Rec: Beyond just using LLMs for feature engineering—who is doing generative recommendation well?
Retrieval vs. Ranking: Any new breakthroughs in the "Two-Tower" paradigm or vector database integration?
Real-world Scale: Papers that address the latency/cost trade-offs of these newer, heavier models.
What has been the most influential paper you’ve read recently that changed how you think about discovery?
The ACM Recommender Systems conference is one of the leading venues in the field. You might check out what papers were accepted for the 2024 and 2025 conferences:
https://recsys.acm.org/