1 citations · 1 across the 5 of their papers we have counts for
5 papers
Every Wrong Answer Counts: Option-Level Psychometrics for LLM Multiple-Choice Benchmarks
Xiao Fei, Yang Zhang, Sarah Almeida Carneiro +1
Most multiple-choice question (MCQ) benchmarks evaluate Large Language Models (LLMs) only by whether they select the correct answers. This binary scoring treats all incorrect respo…
The Masked Advantage: Uncovering Local-Language Access to Cultural Knowledge in LLMs
Yang Zhang, Xiao Fei, Amr Mohamed +6
Large language models are increasingly used to answer culturally grounded questions across languages, yet it remains unclear whether local cultural knowledge is better accessed thr…
CARTE: A Benchmark for Mapping Language Model Knowledge Across France
Sarah Almeida Carneiro, Christos Xypolopoulos, Xiao Fei +2
We introduce CARTE (Culturally Anchored Regional-Territorial Evaluation), a multiple-choice benchmark for evaluating the ability of large language models (LLMs) to discriminate fin…
Clustering Dynamics for Improved Speed Prediction Deriving from Topographical GPS Registrations
Sarah Almeida Carneiro, Giovanni Chierchia, Aurelie Pirayre +1
A persistent challenge in the field of Intelligent Transportation Systems is to extract accurate traffic insights from geographic regions with scarce or no data coverage. To this e…
SWMLP: Shared Weight Multilayer Perceptron for Car Trajectory Speed Prediction using Road Topographical Features
Sarah Almeida Carneiro, Giovanni Chierchia, Jean Charléty +2
Although traffic is one of the massively collected data, it is often only available for specific regions. One concern is that, although there are studies that give good results for…