1 citations · 2 across the 13 of their papers we have counts for
4 papers · 1 filter
OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable?
Liangze Jiang, Damien Teney
Out-of-distribution (OOD) generalization is challenging because distribution shifts come in many forms. Numerous algorithms exist to address specific settings, but choosing the rig…
Scalable Ensemble Diversification for OOD Generalization and Detection
Alexander Rubinstein, Luca Scimeca, Damien Teney +1
Training a diverse ensemble of models has several practical applications such as providing candidates for model selection with better out-of-distribution (OOD) generalization, and…
CulturePark: Boosting Cross-cultural Understanding in Large Language Models
Cheng Li, Damien Teney, Linyi Yang +3
Cultural bias is pervasive in many large language models (LLMs), largely due to the deficiency of data representative of different cultures. Typically, cultural datasets and benchm…
Neural Redshift: Random Networks are not Random Functions
Damien Teney, Armand Nicolicioiu, Valentin Hartmann +1
Our understanding of the generalization capabilities of neural networks (NNs) is still incomplete. Prevailing explanations are based on implicit biases of gradient descent (GD) but…