As many others pointed out, the released files are nearly nothing compared to the full dataset. Personally I've been fiddling a lot with OSINT and analytics over the publicly available Reddit data(a considerable amount of my spare time over the last year) and the one thing I can say is that LLMs are under-performing(huge understatement) - they are borderline useless compared to traditional ML techniques. But as far as LLMs go, the best performers are the open source uncensored models(the most uncensored and unhinged), while the worst performers are the proprietary and paid models, especially over the last 2-3 months: they have been nerfed into oblivion - to the extent where simple prompts like "who is eligible to vote in US presidential elections" is considered a controversial question. So in the unlikely event that the full files are released, I personally would look at the traditional NLP techniques long before investing any time into LLMs.
jellyotsiro|1 month ago
On LLMs vs traditional NLP: I hear you, and I've seen similar issues with LLM hallucination on structured data. That's why the architecture here is hybrid:
- Traditional exact regex/grep search for names, dates, identifiers - Vector search for semantic queries - LLM orchestration layer that must cite sources and can't generate answers without grounding
sebastiennight|1 month ago
"can't" seems like quite a strong claim. Would you care to elaborate?
I can see how one might use a JSON schema that enforces source references in the output, but there is no technique I'm aware of to constrain a model to only come up with data based on the grounding docs, vs. making up a response based on pretrained data (or hallucinating one) and still listing the provided RAG results as attached reference.
It feels like your "can't" would be tantamount to having single-handedly solved the problem of hallucinations, which if you did, would be a billion-dollar-plus unlock for you, so I'm unsure you should show that level of certainty.
spacecadet|1 month ago
plagiarist|1 month ago
tyre|1 month ago
Look for anything that includes the word “woke” in any marketing /tweet material
mariogintili|1 month ago
jellyotsiro|1 month ago
WhitneyLand|1 month ago
"who is eligible to vote in US presidential elections"
pixl97|1 month ago
axegon_|1 month ago
dmos62|1 month ago