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Found 6 papers, 3 papers with code
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
ICL incurs substantial computational, memory, and storage costs because it involves processing all of the training examples every time a prediction is made.
Ranked #1 on
Few-Shot Text Classification
on RAFT
Prosody-Aware Neural Machine Translation for Dubbing
We introduce the task of prosody-aware machine translation which aims at generating translations suitable for dubbing.
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
NLP has achieved great progress in the past decade through the use of neural models and large labeled datasets.
Improving and Simplifying Pattern Exploiting Training
However, PET uses task-specific unlabeled data.
Predicting Institution Hierarchies with Set-based Models
The hierarchical structure of research organizations plays a pivotal role in science of science research as well as in tools that track the research achievements and output.
Optimal Transport-based Alignment of Learned Character Representations for String Similarity
We evaluate STANCE's ability to detect whether two strings can refer to the same entity--a task we term alias detection.
