3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Trust, but Don't Verify: Epistemic Blind Spots in LLM Source Evaluation
Rohan N. Pradhan, Steve Goley
Language models increasingly act as epistemic proxies, synthesizing evidence from multiple sources to inform decisions. Whether they evaluate the quality of that evidence, or merel…
cs.LG2026
Conditional Inference Trees and Forests for Feature Selection
Robert Milletich, Justin Downes, Steve Goley +1
Conditional inference trees (CIT) and conditional inference forests (CIF) reduce split-selection bias by testing features before choosing split thresholds, but repeated permutation…
cs.CV2019★ 3 cited
Unsupervised Feature Learning in Remote Sensing
Aaron Reite, Scott Kangas, Zackery Steck +3
The need for labeled data is among the most common and well-known practical obstacles to deploying deep learning algorithms to solve real-world problems. The current generation of…