DSPy on ICL RAG Classification: Code explained

  Рет қаралды 4,618

code_your_own_AI

code_your_own_AI

5 ай бұрын

Infer-Retrieve-Rank, a new program for extreme multi-label classification, based on DSPy. Infer-Retrieve-Rank achieves state-of-the-art results on three benchmarks using one frozen retriever combine with two in-context learning modules.
These ICL-RAG examples show that the future of prompt and pipeline engineering. Modular DSPy programs, once optimized, can serve as highly effective general-purpose solutions.
Arxiv preprint (all rights with authors):
In-Context Learning for Extreme Multi-Label Classification
arxiv.org/pdf/2401.12178.pdf
Github repo:
github.com/KarelDO/xmc.dspy
#newtechnology
#airesearch

Пікірлер: 9
@rembautimes8808
@rembautimes8808 2 ай бұрын
DSPy is something I came across and love this video on solving the classification problem. Joined as sub
@DreamsAPI
@DreamsAPI 4 ай бұрын
Thank you for making videos about DSPy. Love your style you explain and walk through examples for those of us who don't come from working with pytorch, please continue to make more videos on DSPy going from start to complex that makes you go wow! 🙂
@dayanemarcos1923
@dayanemarcos1923 4 ай бұрын
The potential for high quality data synthesis here is huge
@ghostwhowalks2324
@ghostwhowalks2324 5 ай бұрын
Superb explanation. Thank you. You need to run this program on your video transcripts to label them as well. Such a wealth of knowledge
@kevon217
@kevon217 4 ай бұрын
Agreed!
@TheFxdstudios
@TheFxdstudios 5 ай бұрын
Thank you for sharing this information!
@whig01
@whig01 5 ай бұрын
Apparently you can do classification algorithmically by comparing the Kolmogorov complexity of A+B to that of A and B independently.
@kevon217
@kevon217 5 ай бұрын
Great dall-e generations!
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