From the 2 of 5 papers with an AI index.
5 citations
- Aix-Marseille UniversitéFR5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- École Normale Supérieure de LyonFR1 paper
- Institut de Recherche en Informatique FondamentaleFR1 paper
- Institut Universitaire de FranceFR1 paper
- Laboratoire de l'Informatique du ParallélismeFR1 paper
- Laboratoire de Neurosciences CognitivesFR1 paper
- Laboratoire de Psychologie CognitiveFR1 paper
- Laboratoire d’Informatique Fondamentale de MarseilleFR1 paper
- Max Planck Institute for PsycholinguisticsNL1 paper
- Mohamed bin Zayed University of Artificial IntelligenceAE1 paper
- RIKENJP1 paper
5 papers
How Well Does AI-Generated Feedback Work? Intrinsic and Extrinsic Evaluation across more than 20,000 EFL Essay Drafts
Steven Coyne, Diana Galvan-Sosa, Ryan Spring +4
The paper investigates AI-generated written corrective feedback for English‑as‑a‑Foreign‑Language essays, comparing teacher (intrinsic) ratings with student (extrinsic) responses a…
Explorable Parity Automata
Emile Hazard, Olivier Idir, Denis Kuperberg
The paper introduces explorable automata, a generalization of history‑deterministic automata that resolves nondeterminism using multiple simultaneous runs, and studies their decisi…
Failures and Successes to Learn a Core Conceptual Distinction from the Statistics of Language
Zhimin Hu, Jeroen van Paridon, Gary Lupyan
Generic statements like "tigers are striped" and "cars have radios" communicate information that is, in general, true. However, while the first statement is true in principle, the…
Trees in graphs of large linear cliquewidth
MikoÅaj BojaÅczyk, Pierre Ohlmann
The Pathwidth Theorem states that if a class of graphs has unbounded pathwidth, then it contains all trees as graph minors. We prove a similar result for dense graphs. More precise…
On Quantum Perceptron Learning via Quantum Search
Xiaoyu Sun, Mathieu Roget, Giuseppe Di Molfetta +1
With the growing interest in quantum machine learning, the perceptron, a fundamental building block in traditional machine learning, has emerged as a valuable model for exploring t…