42 citations · 52 across the 3 of their papers we have counts for
6 papers
WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models
Youssef Benchekroun, Megi Dervishi, Mark Ibrahim +7
We propose WorldSense, a benchmark designed to assess the extent to which LLMs are consistently able to sustain tacit world models, by testing how they draw simple inferences from…
GAIA: a benchmark for General AI Assistants
Grégoire Mialon, Clémentine Fourrier, Craig Swift +3
We introduce GAIA, a benchmark for General AI Assistants that, if solved, would represent a milestone in AI research. GAIA proposes real-world questions that require a set of funda…
GraphiT: Encoding Graph Structure in Transformers
Grégoire Mialon, Dexiong Chen, Margot Selosse +1
We show that viewing graphs as sets of node features and incorporating structural and positional information into a transformer architecture is able to outperform representations l…
A Trainable Optimal Transport Embedding for Feature Aggregation and its Relationship to Attention
Grégoire Mialon, Dexiong Chen, Alexandre d'Aspremont +1
We address the problem of learning on sets of features, motivated by the need of performing pooling operations in long biological sequences of varying sizes, with long-range depend…
Screening Data Points in Empirical Risk Minimization via Ellipsoidal Regions and Safe Loss Functions
Grégoire Mialon, Alexandre d'Aspremont, Julien Mairal
We design simple screening tests to automatically discard data samples in empirical risk minimization without losing optimization guarantees. We derive loss functions that produce…
A Kernel Perspective for Regularizing Deep Neural Networks
Alberto Bietti, Grégoire Mialon, Dexiong Chen +1
We propose a new point of view for regularizing deep neural networks by using the norm of a reproducing kernel Hilbert space (RKHS). Even though this norm cannot be computed, it ad…