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 1 (Culturally Anchored Regional-Territorial Evaluation), a multiplechoice benchmark for evaluating the ability of large language models (LLMs) to perform fine-gr…
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…