43 citations · 115 across the 48 of their papers we have counts for
4 papers · 1 filter
Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data
Andrei Margeloiu, Nikola Simidjievski, Pietro Lio +1
Tabular biomedical data is often high-dimensional but with a very small number of samples. Although recent work showed that well-regularised simple neural networks could outperform…
Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations
Shea Cardozo, Gabriel Islas Montero, Dmitry Kazhdan +4
Recent work has suggested post-hoc explainers might be ineffective for detecting spurious correlations in Deep Neural Networks (DNNs). However, we show there are serious weaknesses…
Autoformalization with Large Language Models
Yuhuai Wu, Albert Q. Jiang, Wenda Li +4
Autoformalization is the process of automatically translating from natural language mathematics to formal specifications and proofs. A successful autoformalization system could adv…
Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers
Albert Q. Jiang, Wenda Li, Szymon Tworkowski +5
In theorem proving, the task of selecting useful premises from a large library to unlock the proof of a given conjecture is crucially important. This presents a challenge for all t…