12 citations · 50 across the 23 of their papers we have counts for
32 papers
Low-Rank Prune-And-Factorize for Language Model Compression
Siyu Ren, Kenny Q. Zhu
The components underpinning PLMs -- large weight matrices -- were shown to bear considerable redundancy. Matrix factorization, a well-established technique from matrix theory, has…
Pruning Pre-trained Language Models with Principled Importance and Self-regularization
Siyu Ren, Kenny Q. Zhu
Iterative pruning is one of the most effective compression methods for pre-trained language models. We discovered that finding the optimal pruning decision is an equality-constrain…
Reducing Sensitivity on Speaker Names for Text Generation from Dialogues
Qi Jia, Haifeng Tang, Kenny Q. Zhu
Changing speaker names consistently throughout a dialogue should not affect its meaning and corresponding outputs for text generation from dialogues. However, pre-trained language…
In-sample Curriculum Learning by Sequence Completion for Natural Language Generation
Qi Jia, Yizhu Liu, Haifeng Tang +1
Curriculum learning has shown promising improvements in multiple domains by training machine learning models from easy samples to hard ones. Previous works which either design rule…
Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches and Future Directions
Qi Jia, Yizhu Liu, Siyu Ren +1
Abstractive dialogue summarization is to generate a concise and fluent summary covering the salient information in a dialogue among two or more interlocutors. It has attracted grea…
Few-Shot Natural Language Inference Generation with PDD: Prompt and Dynamic Demonstration
Kaijian Li, Shansan Gong, Kenny Q. Zhu
Natural Language Inference Generation task is to generate a text hypothesis given a text premise and a logical relation between the two. This task can be used in data augmentation…