DSPy on ICL RAG Classification: Code explained

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/...
Github repo:
github.com/Kar...
#newtechnology
#airesearch

[@whig01]

Apparently you can do classification algorithmically by comparing the Kolmogorov complexity of A+B to that of A and B independently.

[@DreamsAPI]

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! 🙂

[@ghostwhowalks2324]

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]

Agreed!

[@dayanemarcos1923]

The potential for high quality data synthesis here is huge

[@TheFxdstudios]

Thank you for sharing this information!

[@rembautimes8808]

DSPy is something I came across and love this video on solving the classification problem. Joined as sub

[@kevon217]

Great dall-e generations!