Reproduce “ReForest: Interpretability Meets Reasoning in Isolation Forest” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Juyoung Seo, Geonwoo Bang, Dongho Kim, Moohong Min
ReForest combines Isolation Forest screening with an LLM that reviews selected records using natural-language accounts of why they were isolated. It adjusts the models’ relative score weights according to IForest’s confidence. On Stroke, recall was 0.27 ± 0.02 versus 0.19 ± 0.00 for IForest, with precision 0.18 ± 0.01 for both; this finding is task-specific.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.