Varun Srinivasan
@v
Interesting misconception that Dan flagged today - people think that we are (or could be) using LLMs for spam detection. With the way LLMs work today, that's like using a hammer to cut your fingernails. LLMs are slow, expensive and don't really have a deep understanding of what spam is in the context of Farcaster. We use a random-forest decision tree that @akshaan designed, and feed it a bunch of signals using embeddings, user actions and graph data.
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Varun Srinivasan
@v
Most of the innovation is at the signal collection layer, and there is some really cool stuff which @notawizard is working on right now. For example: 1. Fraudar: https://bhooi.github.io/papers/fraudar_kdd16.pdf 2. Oddball: https://www.cs.cmu.edu/~mmcgloho/pubs/pakdd10.pdf
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christopher
@christopher
cc @andywon.eth
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Ξric Juta
@ericjuta
@askgina.eth could you try summarise these papers?
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