22 citations · 52 across the 11 of their papers we have counts for
6 papers · 1 filter
Coarse-to-Fine: Hierarchical Multi-task Learning for Natural Language Understanding
Zhaoye Fei, Yu Tian, Yongkang Wu +9
Generalized text representations are the foundation of many natural language understanding tasks. To fully utilize the different corpus, it is inevitable that models need to unders…
Hyperlink-induced Pre-training for Passage Retrieval in Open-domain Question Answering
Jiawei Zhou, Xiaoguang Li, Lifeng Shang +10
To alleviate the data scarcity problem in training question answering systems, recent works propose additional intermediate pre-training for dense passage retrieval (DPR). However,…
KMIR: A Benchmark for Evaluating Knowledge Memorization, Identification and Reasoning Abilities of Language Models
Daniel Gao, Yantao Jia, Lei Li +6
Previous works show the great potential of pre-trained language models (PLMs) for storing a large amount of factual knowledge. However, to figure out whether PLMs can be reliable k…
Towards More Effective and Economic Sparsely-Activated Model
Hao Jiang, Ke Zhan, Jianwei Qu +14
The sparsely-activated models have achieved great success in natural language processing through large-scale parameters and relatively low computational cost, and gradually become…
Early Exiting with Ensemble Internal Classifiers
Tianxiang Sun, Yunhua Zhou, Xiangyang Liu +5
As a simple technique to accelerate inference of large-scale pre-trained models, early exiting has gained much attention in the NLP community. It allows samples to exit early at in…
Emotion Eliciting Machine: Emotion Eliciting Conversation Generation based on Dual Generator
Hao Jiang, Yutao Zhu, Xinyu Zhang +4
Recent years have witnessed great progress on building emotional chatbots. Tremendous methods have been proposed for chatbots to generate responses with given emotions. However, th…