Papers with GRAIN

3 papers
Gradient-based Intra-attention Pruning on Pre-trained Language Models (2023.acl-long)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations