Knowledge Embedding Interface Specification for RAG in NNTrainer - Githubissues

nnstreamer / nntrainer

NNtrainer is Software Framework for Training Neural Network Models on Devices.

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Knowledge Embedding Interface Specification for RAG in NNTrainer #2519

Open hokeun opened 3 months ago

hokeun commented 3 months ago

Preliminary research: Pre-training Knowledge Fusion

Assume that we describe knowledge as Subject-Predicate-Object (SPO) forms.
Delve into and analyze NNTrainer modules that handle user inputs (texts).
Decide whether transformation from the knowledge to the input is necessary, and specify transform(or else) logic from the above knowledge to the inputs if needed.
Devise a few sample scenarios for Question Answering (QA) to analyze the effects of knowledge embeddings (or prompting).

References

AAAI'22 - DKPLM: Decomposable Knowledge-Enhanced Pre-trained Language Model for Natural Language Understanding
EMNLP'22 - Knowledge prompting in pre-trained language model for natural language understanding
EMNLP'19 - Incorporating External Knowledge into Machine Reading for Generative Question Answering

Disclaimer

NOTE: We're open to suggestions. Please let us know in the comments if you have any feedback or guidance!

taos-ci commented 3 months ago

:octocat: cibot: Thank you for posting issue #2519. The person in charge will reply soon.

jijoongmoon commented 3 months ago

Thanks for bringing this topic to NNTrainer. We are happy to help.