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by stared
680 days ago
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From time to time, I see a tool to present a discussion as a tree with arguments for and against it. Unless it is a school essay, arguments don't go that way. It is usually harder to encompass what a node (an atomic fact) is and what a link is (it usually goes beyond "support" and "counter"). Very often, this structure is not a tree. Maybe a DAG with weighted edges, but if it were that straightforward - knowledge graphs would simply work. Instead of rehashing the same tree approach, we should adopt something closer to an LLM-embedding approach - for a given statement, we should have "relevant statements" with an additional dimension if it supports, counters, expands, provides an example, and so on. In this case, it wouldn't even be a DAG. |
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https://umap-learn.readthedocs.io/en/latest/basic_usage.html
> Uniform Manifold Approximation and Projection (UMAP) is a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction. The algorithm is founded on three assumptions about the data
1. The data is uniformly distributed on Riemannian manifold;
2. The Riemannian metric is locally constant (or can be approximated as such);
3. The manifold is locally connected.