4 ms·

It's interesting to see all this hard work being done specifically for "fact-fixing" inside neural networks, whereas I think the future is probably having two m

by dvt 4y ago

It's interesting to see all this hard work being done specifically for "fact-fixing" inside neural networks, whereas I think the future is probably having two models: one for language processing (grammar, etc.) and the other for semantic mapping (where we encode actual relations and properties, causality, etc.). To wit, unless you squint really really hard, this is not exactly true: > Language models can be viewed as knowledge bases containing memorized tuples (s, r, o), each connecting some subject s to an object o via a relation... LLMs don't have the concept of objects or relationships. You might be able to argue some of that ends up being encoded in the embeddings (especially if they're particularly big), but I would posit that those embeddings mostly end up handling the grammar. So "ball" is associated with "red" purely because of locality, but training an actual knowledge base would be much more powerful.

chaxor 4y ago
Do you actually read any literature or are you just saying things for fun? For instance, the work in LLMs "are" knowledge graphs, wherein entire knowledge graphs are extracted from the LLM, or work in ROME which shows that much of the knowledge in relationships exist in the MLPs sections off the NN, or the larger body of works wherein KGs are used in conjunction and trained with the LLM (typically not improving the results to better than sota today), etc. So your statement that it would be more powerful doesn't necessarily stand up in practice, but is a nice theory. Ultimately it's in the details, and it's probably possible to mix explicit "knowledge" with LLMs, but the contextualization of KGs is extremely hard in that scenario, and is handled within the LLM anyway.
- pmoriarty 4y ago
  As someone with little knowledge about this field, I am curious what "ROME" and "sota" refer to.
  - gattilorenz 4y ago
    Sota is “state of the art”. ROME seems to be the technique previously introduced by the authors of the paper in the post

by dvt 4y ago

chaxor 4y ago

Do you actually read any literature or are you just saying things for fun? For instance, the work in LLMs "are" knowledge graphs, wherein entire knowledge graphs are extracted from the LLM, or work in ROME which shows that much of the knowledge in relationships exist in the MLPs sections off the NN, or the larger body of works wherein KGs are used in conjunction and trained with the LLM (typically not improving the results to better than sota today), etc. So your statement that it would be more powerful doesn't necessarily stand up in practice, but is a nice theory. Ultimately it's in the details, and it's probably possible to mix explicit "knowledge" with LLMs, but the contextualization of KGs is extremely hard in that scenario, and is handled within the LLM anyway.

pmoriarty 4y ago
As someone with little knowledge about this field, I am curious what "ROME" and "sota" refer to.
- gattilorenz 4y ago
  Sota is “state of the art”. ROME seems to be the technique previously introduced by the authors of the paper in the post