Papers with GRAIN
Gradient-based Intra-attention Pruning on Pre-trained Language Models (2023.acl-long)
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| Challenge: | Pre-trained language models are computationally expensive and slow in inference due to their large sizes. |
| Approach: | They propose a structured pruning method which combines pruning with knowledge distillation to yield highly effective models. |
| Outcome: | The proposed method outperforms other pruning methods in sparsity regimes while maintaining 93% 99% performance. |
German Radio Interviews: The GRAIN Release of the SFB732 Silver Standard Collection (L18-1)
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Katrin Schweitzer, Kerstin Eckart, Markus Gärtner, Agnieszka Falenska, Arndt Riester, Ina Rösiger, Antje Schweitzer, Sabrina Stehwien, Jonas Kuhn
| Challenge: | GRAIN contains German radio interviews and is annotated on multiple linguistic layers. |
| Approach: | They present GRAIN as part of the SFB732 Silver Standard Collection . GRAIN contains German radio interviews and is annotated on multiple linguistic layers . |
| Outcome: | The GRAIN data set contains German radio interviews and is annotated on multiple linguistic layers. |
GRAIN-S: Manually Annotated Syntax for German Interviews (2020.lrec-1)
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| Challenge: | GRAIN-S is a set of manually created syntactic annotations for radio interviews in germany. |
| Approach: | They propose to use GRAIN-S to create syntactic annotations for radio interviews in germany. |
| Outcome: | The proposed dataset extends an existing corpus GRAIN and comes with constituency and dependency trees for six interviews. |