The relevance here is pretty weak.
https://sturdystatistics.com/deepdive?fast=0&q=reinforcement...
I think only 1/10 of the articles is really on topic.
The relevance here is pretty weak.
https://sturdystatistics.com/deepdive?fast=0&q=reinforcement...
I think only 1/10 of the articles is really on topic.
I see that the model has not yet finished training: I think you are referring to the "Raw Search Results Section".
Our tool works a little different than LLM style tools. We are doing a bulk search — for academic search, ~1000 papers — and then training a hierarchical Bayesian model to organize the results. Once the model trains, it provides a visual representation of the high level themes that you can then use to explore the results.
The trade off is we are willing to lower the relevance filter to enable a broad set of exploration.