37 citations · 38 across the 6 of their papers we have counts for
6 papers
Consistency-based Abductive Reasoning over Perceptual Errors of Multiple Pre-trained Models in Novel Environments
Mario Leiva, Noel Ngu, Joshua Shay Kricheli +6
The deployment of pre-trained perception models in novel environments often leads to performance degradation due to distributional shifts. Although recent artificial intelligence a…
VLC Fusion: Vision-Language Conditioned Sensor Fusion for Robust Object Detection
Aditya Taparia, Noel Ngu, Mario Leiva +6
Although fusing multiple sensor modalities can enhance object detection performance, existing fusion approaches often overlook subtle variations in environmental conditions and sen…
Multiple Distribution Shift -- Aerial (MDS-A): A Dataset for Test-Time Error Detection and Model Adaptation
Noel Ngu, Aditya Taparia, Gerardo I. Simari +5
Machine learning models assume that training and test samples are drawn from the same distribution. As such, significant differences between training and test distributions often l…
Metal Price Spike Prediction via a Neurosymbolic Ensemble Approach
Nathaniel Lee, Noel Ngu, Harshdeep Singh Sahdev +4
Predicting price spikes in critical metals such as Cobalt, Copper, Magnesium, and Nickel is crucial for mitigating economic risks associated with global trends like the energy tran…
Diversity Measures: Domain-Independent Proxies for Failure in Language Model Queries
Noel Ngu, Nathaniel Lee, Paulo Shakarian
Error prediction in large language models often relies on domain-specific information. In this paper, we present measures for quantification of error in the response of a large lan…
An Independent Evaluation of ChatGPT on Mathematical Word Problems (MWP)
Paulo Shakarian, Abhinav Koyyalamudi, Noel Ngu +1
We study the performance of a commercially available large language model (LLM) known as ChatGPT on math word problems (MWPs) from the dataset DRAW-1K. To our knowledge, this is th…