RecRanker and RecLM

RecRanker
35
Emerging
RecLM
33
Emerging
Maintenance 0/25
Adoption 6/25
Maturity 16/25
Community 13/25
Maintenance 2/25
Adoption 9/25
Maturity 8/25
Community 14/25
Stars: 16
Forks: 3
Downloads: —
Commits (30d): 0
Language: Python
License: GPL-3.0
Stars: 109
Forks: 13
Downloads: —
Commits (30d): 0
Language: Python
License: —
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About RecRanker

sichunluo/RecRanker

[TOIS'24] "RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation"

This project helps e-commerce sites, streaming services, or content platforms improve their product recommendation systems. It takes information about user preferences and items, then outputs a personalized, ordered list of top recommendations for each user. This is designed for machine learning engineers or data scientists working on recommender systems.

e-commerce recommendations content discovery personalized ranking machine learning engineering data science

About RecLM

HKUDS/RecLM

[ACL2025] "RecLM: Recommendation Instruction Tuning"

This project helps optimize recommendation systems, especially when you don't have much data about new users or items. It takes your existing user interaction data and item descriptions, then uses advanced language models and reinforcement learning to create more accurate user and item profiles. The output is enhanced profiles that plug into your current recommendation engine, helping it make better suggestions. This is for data scientists or machine learning engineers building and maintaining recommendation systems.

recommendation-systems cold-start-problem user-profiling item-profiling machine-learning-engineering

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