research
∙
07/30/2023
Unified Model for Image, Video, Audio and Language Tasks
Large Language Models (LLMs) have made the ambitious quest for generalis...
share
research
∙
06/07/2023
Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards
Foundation models are first pre-trained on vast unsupervised datasets an...
research
∙
12/20/2022
Recycling diverse models for out-of-distribution generalization
Foundation models are redefining how AI systems are built. Practitioners...
research
∙
05/20/2022
Towards efficient feature sharing in MIMO architectures
Multi-input multi-output architectures propose to train multiple subnetw...
research
∙
05/19/2022
Diverse Weight Averaging for Out-of-Distribution Generalization
Standard neural networks struggle to generalize under distribution shift...
research
∙
11/22/2021
DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion
Deep network architectures struggle to continually learn new tasks witho...
research
∙
09/07/2021
Fishr: Invariant Gradient Variances for Out-of-distribution Generalization
Learning robust models that generalize well under changes in the data di...
research
∙
03/10/2021
MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworks
Recent strategies achieved ensembling "for free" by fitting concurrently...
research
∙
01/14/2021
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation
Deep ensembles perform better than a single network thanks to the divers...
research
∙
10/06/2020
CORE: Color Regression for Multiple Colors Fashion Garments
Among all fashion attributes, color is challenging to detect due to its ...
research
∙
12/06/2018
OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation
Object detectors tend to perform poorly in new or open domains, and requ...
research
∙
09/27/2017
