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I am an indie researcher working on information retrieval for LLMs. It Involves building better Dense, Sparse and Hybrid Representations enable RAGs for LLMs

  • SPLADE Models
  • MiniMiracle
  • FlashRank
  • Google Scholar
  • I am an Independent intersectional MLE / Researcher. it's hard to sustain ongoing AI research which is a compute-heavy endeavor, Your sponsorship would directly contribute to the research.
  • I am actively working on Hybrid search which is better than just vector search. I don't stop at the dogma of research, I have also built and scaled real-world apps based on my research findings in hybrid search so far (fx https://savelikeapro.ai).
  • Problems like what is the best way to chunk your data for a RAG use-case is not yet fully solved.
  • I am actively working on some of the pertinent problems in the world of LLMs like better cheaper inference and Hallucination detection.

Thank you
Prithivi Da

@PrithivirajDamodaran

It would mean a world to have smarter like-minded people seeing value and supporting my work

Featured sponsors

@dan10000
@maruthiprithivi
Private Sponsor
@limkimki
Past sponsors 4
@limkimki
@maruthiprithivi
@dan10000
Private Sponsor

Featured work

  1. PrithivirajDamodaran/FlashRank

    Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & C…

    Python 661
  2. PrithivirajDamodaran/Parrot_Paraphraser

    A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull reque…

    Python 879
  3. PrithivirajDamodaran/Gramformer

    A framework for detecting, highlighting and correcting grammatical errors on natural language text. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.

    Python 1,505
  4. PrithivirajDamodaran/Styleformer

    A Neural Language Style Transfer framework to transfer natural language text smoothly between fine-grained language styles like formal/casual, active/passive, and many more. Created by Prithiviraj …

    Python 479

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