17 citations · 105 across the 32 of their papers we have counts for
6 papers · 1 filter
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…
Leaner and Faster: Two-Stage Model Compression for Lightweight Text-Image Retrieval
Siyu Ren, Kenny Q. Zhu
Current text-image approaches (e.g., CLIP) typically adopt dual-encoder architecture using pre-trained vision-language representation. However, these models still pose non-trivial…
Post-Training Dialogue Summarization using Pseudo-Paraphrasing
Qi Jia, Yizhu Liu, Haifeng Tang +1
Previous dialogue summarization techniques adapt large language models pretrained on the narrative text by injecting dialogue-specific features into the models. These features eith…
Modeling Multi-level Context for Informational Bias Detection by Contrastive Learning and Sentential Graph Network
Shijia Guo, Kenny Q. Zhu
Informational bias is widely present in news articles. It refers to providing one-sided, selective or suggestive information of specific aspects of certain entity to guide a specif…