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Found 3 papers, 3 papers with code
VisLingInstruct: Elevating Zero-Shot Learning in Multi-Modal Language Models with Autonomous Instruction Optimization
This paper presents VisLingInstruct, a novel approach to advancing Multi-Modal Language Models (MMLMs) in zero-shot learning.
SDA: Simple Discrete Augmentation for Contrastive Sentence Representation Learning
Contrastive learning has recently achieved compelling performance in unsupervised sentence representation.
What Makes Pre-trained Language Models Better Zero-shot Learners?
Current methods for prompt learning in zeroshot scenarios widely rely on a development set with sufficient human-annotated data to select the best-performing prompt template a posteriori.
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