HN Explorer

mingtianzhang

↗ HN profile [ 71.0 ms ] full profile
Karma
0
Created
()
Submissions
0
  1. Show HN: We Built a Chat of Stanford's CS229 Course Notes

    CS229 is one of the most widely referenced machine learning courses. I turned the complete course notes into a searchable knowledge base with citations back to the original source material. The goal is to make long…

    2 points 0
  2. 1 points 0
  3. 1 points 0
  4. Show HN: Open KB: Open LLM Knowledge Base

    We release an open source version of Andrej Karparthy's open knowledge base, and we scale it to support long PDFs with Pageindex. Any feedback is welcome to help us improve this project! Github repo:…

    6 points 1
  5. ClawdReview – OpenReview for AI Agents

    Agents can review the paper on arXiv, and humans can like or dislike agents' reviews. There are also ranking lists of the most popular papers and agents. Please visit: https://clawdreview.ai/

    5 points 0
  6. Show HN: ClawdReview – OpenReview for AI Agents

    Agents can review the paper on arXiv, and humans can like or dislike agents' reviews. There are also ranking lists of the most popular papers and agents. Please visit: https://clawdreview.ai/

    3 points 0
  7. 1 points 0
  8. 1 points 0
  9. 1 points 0
  10. 1 points 0
  11. 1 points 1
  12. 1 points 0
  13. 1 points 0
  14. Do we still need OCR? An implementation of a pure vision-based agent (pageindex.ai)
    7 points 1
  15. Do We Still Need OCR? (pageindex.ai)
    4 points 2
  16. Reasoning-based RAG for long document question answering (pageindex.ai)
    1 points 1
  17. PageIndex Chat – Human-Like Long Document AI Analyst (pageindex.ai)
    6 points 1
  18. PageIndex Chat – Human-Like Long Document AI Analyst (pageindex.ai)
    4 points 1
  19. Show HN: In-Context Index for In-Context Retrieval (github.com)

    RAG pipelines have become bloated: embeddings, vector DBs, rerankers, and ad-hoc pipelines everywhere. Projects like Claude Code showed a simpler path: In-Context Retrieval — letting the LLM reason directly over context…

    5 points 0
  20. DeepMind's paper reveals Google's new direction on RAG: In-Context Retreival (arxiv.org)
    6 points 1
  21. From Claude Code to Agentic RAG (vectifyai.notion.site)
    3 points 0
  22. From Claude Code to PageIndex: The Rise of Agentic Retrieval (vectifyai.notion.site)
    3 points 1
  23. From Claude Code to PageIndex: The Rise of Agentic Retrieval (vectifyai.notion.site)
    8 points 0
  24. Show HN: PageIndex for Reasoning-Based RAG (vectifyai.notion.site)

    In this blog, we introduce a pure JSON index to enable reasoning-based RAG without relying on any Vector DBs. Any feedback is welcome!

    6 points 0
  25. Show HN: A Vectorless LLM-Native Document Index Method (github.com)

    The word "index" originally came from how humans retrieve info: book indexes and tables of contents that guide us to the right place in documents. Computers later borrowed the term for data structures: e.g., B-trees,…

    14 points 1