LAION-AI / LAION-AI/Open-Assistant
Crowdsource data normalization
Open
Nobody has claimed this yet.
data
ml
- Dominant language
- Python
- Stars
- 37.4k
- Forks
- 3.3k
- PR merge metrics
- No merged PRs in 30d
Description
Users will add have tendencies on how they score things (for example, some might put something helpful at 4, and only use 5 early) To account for this, in addition to asking multiple users, it should first normalize the scoring to how that user's response compares to others.
Contributor guide
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
No files, tests, or entry points are identified in the issue. First define the per-user normalization method, how it integrates with the existing scoring flow, and how multiple users' responses should be combined; done should include an agreed algorithm and validation that normalized scores address the stated user-bias example.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100