6 days ago · Empirically, CMTR outperforms SOTA multi-task learning frameworks on most natural language understanding tasks in the GLUE benchmark.

Experimental results show that CMTR outperforms other state-of-the-art multi-task learning approaches for NLU. Meanwhile, the model also shows superior ...

5 days ago · Abstract: Multi-task learning has shown large benefits in Natural Language Understanding (NLU). However, current state-of-the-arts (SOTAs) like ...

Missing: Collaborative | Show results with:Collaborative

This PyTorch package implements the Multi-Task Deep Neural Networks (MT-DNN) for Natural Language Understanding

Oct 12, 2022 · Inspired by human learning, multi-task learning believes that tasks can interact and boost each other. Therefore, to obtain a more robust ...

A Multi-Task Deep Neural Network (MT-DNN) for learning representations across multiple natural language understanding (NLU) tasks that allows domain adaptation.

Multi-Task Learning (MTL) By exploiting commonalities and differences among relevant tasks, MTL can enhance learning efficiency and improve prediction accuracy ...

Jul 25, 2024 · In this article, we give an overview of the use of MTL in NLP tasks. We first review MTL architectures used in NLP tasks and categorize them into four classes.

Collaborative Multi-Task Representation for Natural Language Understanding. Conference Paper. Jun 2024. Yaming Yang · Defu Cao · Ming Zeng ...