5 ms·

Could you explain or link to explanations of all of the acronyms you’ve used in your comment?

jiggawatts 2y ago
It makes me chuckle a bit to see this kind of request in a tech forum, particularly when discussing advanced LLM-related topics. This is akin to a HN comment asking someone to search the Internet for something on their behalf, while discussing search engine algorithms!
- williamcotton 2y ago
  It adds useful context to the discussion and spurs further conversation.
  - williamcotton 2y ago
    HyDE: Hypothetical Document Embeddings [1] RAGAS: RAG Assessment [2] RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval [3] Self-RAG: Self-Reflective Retrieval-Augmented Generation [4] Agentic RAG: Agentic Retrieval-Augmented Generation [5] GraphRAG: Graph Retrieval-Augmented Generation [6] [1] https://docs.haystack.deepset.ai/docs/hypothetical-document-embeddings-hyde https://docs.haystack.deepset.ai/docs/hypothetical-document-... [2] https://docs.ragas.io/en/stable/ https://docs.ragas.io/en/stable/ [3] https://arxiv.org/html/2401.18059v1 https://arxiv.org/html/2401.18059v1 [4] https://selfrag.github.io https://selfrag.github.io [5] https://langchain-ai.github.io/langgraph/tutorials/rag/langgraph_agentic_rag/ https://langchain-ai.github.io/langgraph/tutorials/rag/langg... [6] https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/ https://www.microsoft.com/en-us/research/blog/graphrag-unloc...
- _kb 2y ago
  A lot of people here (myself included) work across different specialisations and are here to learn from discussion that is intentionally unfamiliar.
  - jiggawatts 2y ago
    Yes, but ChatGPT knows these things! Just ask it to expand the acronyms. This is the new “can you Google that for me?”
    - _kb 2y ago
      يمكن لـ ChatGPT أيضًا الترجمة من العربية إلى الإنجليزية، ولكن سيكون من المزعج استخدامه للمحادثة في هذا السياق
      - jiggawatts 2y ago
        Annyira lusta vagyok, hogy nem akarok néhány gombot megnyomni, ezért kérlek, írj nekem egy oldal szöveget.
    - cubefox 2y ago
      Another solution is to downvote / not upvote comments which place an unreasonable burden on the reader. The best comments are those which can be broadly understood without a need for Googling acronyms or "expanding" the comment using an LLM.
santiagobasulto 2y ago
These are all "techniques" on top of the foundations of RAG. It's similar to "Chain of Thought" in prompt engineering. You have an underlying technology, and then come up with techniques/frameworks on top. What MVC was for Web dev +15 years ago. RAPTOR for example is a technique that groups and clusters documents together, summarizes them, and creates embeddings defining a sort of a Tree. Paper: https://arxiv.org/html/2401.18059v1 https://arxiv.org/html/2401.18059v1 Agentic RAG is creating an agent that can decide to augment "conversations" (or other LLM tools) with RAG searches and analyze its relevance. Pretty useful, but hard to implement right. You can google the others, they're all more or less these "techniques" to improve an old-fashioned RAG search.
- captaindiego 2y ago
  Worth noting that a lot of the improvement gains you get from RAPTOR are (from my use cases) related to giving context to the chunks. Simpler but easier to implement methods of summarizing context (e.g. in a hierarchical document) and cutting chunks around document boundaries can get you most of the way there with less effort (again, as other mentioned, it depends though on your use)

It makes me chuckle a bit to see this kind of request in a tech forum, particularly when discussing advanced LLM-related topics. This is akin to a HN comment asking someone to search the Internet for something on their behalf, while discussing search engine algorithms!

williamcotton 2y ago
It adds useful context to the discussion and spurs further conversation.
- williamcotton 2y ago
  HyDE: Hypothetical Document Embeddings [1] RAGAS: RAG Assessment [2] RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval [3] Self-RAG: Self-Reflective Retrieval-Augmented Generation [4] Agentic RAG: Agentic Retrieval-Augmented Generation [5] GraphRAG: Graph Retrieval-Augmented Generation [6] [1] https://docs.haystack.deepset.ai/docs/hypothetical-document-embeddings-hyde https://docs.haystack.deepset.ai/docs/hypothetical-document-... [2] https://docs.ragas.io/en/stable/ https://docs.ragas.io/en/stable/ [3] https://arxiv.org/html/2401.18059v1 https://arxiv.org/html/2401.18059v1 [4] https://selfrag.github.io https://selfrag.github.io [5] https://langchain-ai.github.io/langgraph/tutorials/rag/langgraph_agentic_rag/ https://langchain-ai.github.io/langgraph/tutorials/rag/langg... [6] https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/ https://www.microsoft.com/en-us/research/blog/graphrag-unloc...
_kb 2y ago
A lot of people here (myself included) work across different specialisations and are here to learn from discussion that is intentionally unfamiliar.
- jiggawatts 2y ago
  Yes, but ChatGPT knows these things! Just ask it to expand the acronyms. This is the new “can you Google that for me?”
  - _kb 2y ago
    يمكن لـ ChatGPT أيضًا الترجمة من العربية إلى الإنجليزية، ولكن سيكون من المزعج استخدامه للمحادثة في هذا السياق
    - jiggawatts 2y ago
      Annyira lusta vagyok, hogy nem akarok néhány gombot megnyomni, ezért kérlek, írj nekem egy oldal szöveget.
  - cubefox 2y ago
    Another solution is to downvote / not upvote comments which place an unreasonable burden on the reader. The best comments are those which can be broadly understood without a need for Googling acronyms or "expanding" the comment using an LLM.

santiagobasulto 2y ago

These are all "techniques" on top of the foundations of RAG. It's similar to "Chain of Thought" in prompt engineering. You have an underlying technology, and then come up with techniques/frameworks on top. What MVC was for Web dev +15 years ago. RAPTOR for example is a technique that groups and clusters documents together, summarizes them, and creates embeddings defining a sort of a Tree. Paper: https://arxiv.org/html/2401.18059v1 https://arxiv.org/html/2401.18059v1 Agentic RAG is creating an agent that can decide to augment "conversations" (or other LLM tools) with RAG searches and analyze its relevance. Pretty useful, but hard to implement right. You can google the others, they're all more or less these "techniques" to improve an old-fashioned RAG search.

captaindiego 2y ago
Worth noting that a lot of the improvement gains you get from RAPTOR are (from my use cases) related to giving context to the chunks. Simpler but easier to implement methods of summarizing context (e.g. in a hierarchical document) and cutting chunks around document boundaries can get you most of the way there with less effort (again, as other mentioned, it depends though on your use)