30 citations · 76 across the 26 of their papers we have counts for
7 papers · 1 filter
Usefulness of LLMs as an Author Checklist Assistant for Scientific Papers: NeurIPS'24 Experiment
Alexander Goldberg, Ihsan Ullah, Thanh Gia Hieu Khuong +4
Large language models (LLMs) represent a promising, but controversial, tool in aiding scientific peer review. This study evaluates the usefulness of LLMs in a conference setting as…
FAIR Universe HiggsML Uncertainty Dataset and Competition
Lisa Benato, Wahid Bhimji, Paolo Calafiura +26
The FAIR Universe HiggsML Uncertainty Challenge focused on measuring the physical properties of elementary particles with imperfect simulators. Participants were required to comput…
SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge
Hao Ding, Yuqian Zhang, Tuxun Lu +39
Surgical data science has seen rapid advancement with the excellent performance of end-to-end deep neural networks (DNNs). Despite their successes, DNNs have been proven susceptibl…
RelevAI-Reviewer: A Benchmark on AI Reviewers for Survey Paper Relevance
Paulo Henrique Couto, Quang Phuoc Ho, Nageeta Kumari +4
Recent advancements in Artificial Intelligence (AI), particularly the widespread adoption of Large Language Models (LLMs), have significantly enhanced text analysis capabilities. T…
Depth Estimation using Weighted-loss and Transfer Learning
Muhammad Adeel Hafeez, Michael G. Madden, Ganesh Sistu +1
Depth estimation from 2D images is a common computer vision task that has applications in many fields including autonomous vehicles, scene understanding and robotics. The accuracy…
Beyond the Known: Adversarial Autoencoders in Novelty Detection
Muhammad Asad, Ihsan Ullah, Ganesh Sistu +1
In novelty detection, the goal is to decide if a new data point should be categorized as an inlier or an outlier, given a training dataset that primarily captures the inlier distri…