LAION-AI / LAION-AI/temporal-embedding-aggregation
Research Priority Queue
Open
Nobody has claimed this yet.
research
- Dominant language
- Python
- Stars
- 32
- Forks
- 4
- PR merge metrics
- No merged PRs in 30d
Description
- More Benchmarks (https://github.com/LAION-AI/temporal-embedding-aggregation/issues/33)
- Test Different CLIP backbones (https://github.com/LAION-AI/temporal-embedding-aggregation/issues/36)
- Hyperparameter sweep for simple aggregator like self attention (https://github.com/LAION-AI/temporal-embedding-aggregation/issues/37)
- Architecture tuning (https://github.com/LAION-AI/temporal-embedding-aggregation/issues/38)
- video-clip guided stable diffusion (https://github.com/LAION-AI/temporal-embedding-aggregation/issues/39)
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Review the unchecked linked issues for More Benchmarks (#33), hyperparameter sweeps (#37), architecture tuning (#38), and video-CLIP-guided stable diffusion (#39), using the completed backbone item (#36) as context. The queue is done when the remaining research priorities are resolved or otherwise updated with clear outcomes.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100