mirror of
https://github.com/wassname/stampy-chat.git
synced 2026-09-22 13:40:44 +08:00
30 lines
1.5 KiB
Markdown
30 lines
1.5 KiB
Markdown
# AlignmentSearch
|
|
|
|
This project creates embeddings for every set of a few paragraphs from the source dataset, in order to do real-time semantic search and question answering on them.
|
|
|
|
The very barebones of the project is currently in testing.ipynb.
|
|
|
|
## TODO:
|
|
- Getting data:
|
|
- Figure out the right format for the dataset
|
|
- Get entirety of data
|
|
- Searches for new posts/papers/etc and scrape them, runs once a day
|
|
- Semantic search:
|
|
- Test out other techniques than just vector similarity (e.g. LSH-index, see Dense Retrieval methods (here)[https://medium.com/@aikho/deep-learning-in-information-retrieval-part-ii-dense-retrieval-1f9fecb47de9])
|
|
- Test other embeddings models ((SimCSE)[https://github.com/princeton-nlp/SimCSE] possibly SOTA?)
|
|
- Question answering:
|
|
- Test out other models prompts to see which is best
|
|
- Summarization:
|
|
- Test out other models and prompts to see which is best (Forefront?)
|
|
- Info extraction from PDF:
|
|
- Specifically mentioned by Anson. Look into methods by Mely.ai to extract tables from PDFs maybe?
|
|
- Test various techniques to make it more performant
|
|
- Finetuning:
|
|
- Finetune embeddings model
|
|
- Finetune q&a model
|
|
- Finetune summarization model
|
|
- Finetune info extraction model
|
|
- Create website/other. Not sure what would be most helpful here
|
|
- Find someone that can figure this out
|
|
|
|
Source dataset: Kirchner, J. H., Smith, L., Thibodeau, J., McDonnell, K., and Reynolds, L. "Understanding AI alignment research: A Systematic Analysis." arXiv preprint arXiv:2022.4338861 (2022). |