LLMRec
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation" (by HKUDS)
graph-progression
Create a progression of recommendations from a user-supplied recommender (by askarthur)
LLMRec | graph-progression | |
---|---|---|
1 | 1 | |
258 | 1 | |
- | - | |
8.8 | 0.0 | |
12 days ago | almost 2 years ago | |
Python | Python | |
- | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
LLMRec
Posts with mentions or reviews of LLMRec.
We have used some of these posts to build our list of alternatives
and similar projects.
graph-progression
Posts with mentions or reviews of graph-progression.
We have used some of these posts to build our list of alternatives
and similar projects.
-
Create a progression of recommendations with any recommender
Hi! For work I made a recommendation progression package which we've open sourced! Let me explain.
What are some alternatives?
When comparing LLMRec and graph-progression you can also consider the following projects:
torchrec - Pytorch domain library for recommendation systems
algorithmx-python - A library for network visualization and algorithm simulation.
recommenders - Best Practices on Recommendation Systems
implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets