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20222026
most citedTokenization Consistency Matters for Generative Models on Extractive NLP Tasks

2 citations · 2 across the 5 of their papers we have counts for

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cs.CL2022

Improving Cross-task Generalization of Unified Table-to-text Models with Compositional Task Configurations

Jifan Chen, Yuhao Zhang, Lan Liu +5

There has been great progress in unifying various table-to-text tasks using a single encoder-decoder model trained via multi-task learning (Xie et al., 2022). However, existing met…

cs.CL2022★ 2 cited

Tokenization Consistency Matters for Generative Models on Extractive NLP Tasks

Kaiser Sun, Peng Qi, Yuhao Zhang +3

Generative models have been widely applied to solve extractive tasks, where parts of the input is extracted to form the desired output, and achieved significant success. For exampl…