Africa
Generalizing Consistency Policy to Visual RL with Prioritized Proximal Experience Regularization
With high-dimensional state spaces, visual reinforcement learning (RL) faces significant challenges in exploitation and exploration, resulting in low sample efficiency and training stability.
Scale Equivariant Graph Metanetworks
This paper pertains to an emerging machine learning paradigm: learning higher-order functions, i.e. functions whose inputs are functions themselves, particularly
BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack
To bridge this gap, we introduce the BABILong benchmark, designed to test language models' ability to reason across facts distributed in extremely
No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models Angรฉline Pouget
Second, pretraining with global, unfiltered data before fine-tuning on English content can improve cultural understanding without sacrificing performance on said popular benchmarks.
Mitigating Biases in Blackbox Feature Extractors for Image Classification Tasks
In image classification, it is common to utilize a pretrained model to extract meaningful features of the input images, and then to train a classifier on top of it to make predictions for any downstream task.
Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes
The mixed regime is the'best of both worlds': it converges
