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Found 5 papers, 5 papers with code
Benchmarking Low-Shot Robustness to Natural Distribution Shifts
Robustness to natural distribution shifts has seen remarkable progress thanks to recent pre-training strategies combined with better fine-tuning methods.
Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking Consistency
Inspired by the design of recent SSL approaches based on learning from partial image inputs generated via masking or cropping -- either by learning to predict the missing pixels, or learning representational invariances to such augmentations -- we propose PACMAC, a simple two-stage adaptation algorithm for self-supervised ViTs.
Data Distributional Properties Drive Emergent In-Context Learning in Transformers
In further experiments, we found that naturalistic data distributions were only able to elicit in-context learning in transformers, and not in recurrent models.
SAFIN: Arbitrary Style Transfer With Self-Attentive Factorized Instance Normalization
We demonstrate that plugging SAFIN into the base network of another state-of-the-art method results in enhanced stylization.
An End-to-End Network for Emotion-Cause Pair Extraction
The task of Emotion-Cause Pair Extraction (ECPE) aims to extract all potential clause-pairs of emotions and their corresponding causes in a document.
