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Found 2 papers, 1 papers with code
Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering
However, most prior works assume that all the tasks are sampled from a single data source, which cannot adapt to real-world scenarios where tasks are heterogeneous and lie in different distributions.
Eliciting and Understanding Cross-Task Skills with Task-Level Mixture-of-Experts
Recent works suggest that transformer models are capable of multi-tasking on diverse NLP tasks and adapting to new tasks efficiently.
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