recommendationfamily
GRU4Rec
Session-based recommendation with recurrent neural networks. Paper by Hidasi et al. (2015).
Levelfamily
Classrecommendation
Parametersnot in the notes
Contextnot in the notes
Released21 Nov 2015
Opennessunknown
Runs onnot in the notes
Statusactive
Identity
- Developer
- Gravity R&D
- Family
- not in the notes
- Released
- 21 Nov 2015 sourcesannouncement page
- Weights published
- –
- Record checked
- 12 Oct 2026
Where this comes from
Developer and dates from the research notes. Release date is the vendor's public announcement; weights date is when open weights were published.
Architecture and Size
- Architecture
- other Recurrent network with GRU cells over session clicks
- Total parameters
- – sources
- Active parameters
- –
- Checkpoint parameters
- –
- Context length
- not in the notes
- Input
- table
- Output
- table
Where this comes from
Parameter counts as the developer states them. Where the checkpoint holds a different total, both are shown (register A16).
Openness and Access
- Openness
- unknown
- Licence
- not in the notes sources
- Access routes
- not in the notes
Where this comes from
The licence file governs over registry tags and aggregator labels.
Deployment
- Runs on
- not in the notes
- Footprint
- Reference repository hidasib/GRU4Rec has no standard licence identified by GitHub; RecBole implementation is MIT.
- Runtimes
- not in the notes
Where this comes from
Deployment tiers and runtimes as named in the notes. Footprint is the notes' figure, not a measurement by AURION.
Indonesia
- Indonesian support
- not stated
- Regional languages
- not in the notes
- Jakarta hosting
- unknown
- Languages
- not in the notes
Where this comes from
Indonesia fields are carried on every model; unknown is an allowed value.
Benchmark Results
The notes record no benchmark result for this model.
Lineage
The notes record no lineage for this model.
Industry Use Cases
No industry use case links this model.
Links
DeveloperGravity R&Dcompany
ModelGRU4RecGravity R&D, recommendation
Use CasesSuper-App Recommendation and PersonalisationRetail and LogisticsUse cases of models in the same R&D topic; none is recorded for this model itself.
Who Runs It
GrabIn production, 6 Oct 2026Deployments of these use cases; none names this model.
GrabIn production, 6 Oct 2026Deployments of these use cases; none names this model.Organisations 1
Sources
- arxiv.org/abs/1511.06939 https://arxiv.org/abs/1511.06939
- github.com/hidasib/GRU4Rec https://github.com/hidasib/GRU4Rec
- github.com/RUCAIBox/RecBole2.0/blob/main/model_list.md https://github.com/RUCAIBox/RecBole2.0/blob/main/model_list.md
- arxiv.org/html/1511.06939 https://arxiv.org/html/1511.06939
To cite this page: Project AURION, AI Use-Cases Research & Innovation, "GRU4Rec", https://aurion.semai.id/models/gru4rec/, records of October 2026.