45 citations · 307 across the 59 of their papers we have counts for
6 papers · 1 filter
HopRetriever: Retrieve Hops over Wikipedia to Answer Complex Questions
Shaobo Li, Xiaoguang Li, Lifeng Shang +5
Collecting supporting evidence from large corpora of text (e.g., Wikipedia) is of great challenge for open-domain Question Answering (QA). Especially, for multi-hop open-domain QA,…
Improving Task-Agnostic BERT Distillation with Layer Mapping Search
Xiaoqi Jiao, Huating Chang, Yichun Yin +6
Knowledge distillation (KD) which transfers the knowledge from a large teacher model to a small student model, has been widely used to compress the BERT model recently. Besides the…
PPKE: Knowledge Representation Learning by Path-based Pre-training
Bin He, Di Zhou, Jing Xie +3
Entities may have complex interactions in a knowledge graph (KG), such as multi-step relationships, which can be viewed as graph contextual information of the entities. Traditional…
KgPLM: Knowledge-guided Language Model Pre-training via Generative and Discriminative Learning
Bin He, Xin Jiang, Jinghui Xiao +1
Recent studies on pre-trained language models have demonstrated their ability to capture factual knowledge and applications in knowledge-aware downstream tasks. In this work, we pr…
BinaryBERT: Pushing the Limit of BERT Quantization
Haoli Bai, Wei Zhang, Lu Hou +6
The rapid development of large pre-trained language models has greatly increased the demand for model compression techniques, among which quantization is a popular solution. In thi…
Better Robustness by More Coverage: Adversarial Training with Mixup Augmentation for Robust Fine-tuning
Chenglei Si, Zhengyan Zhang, Fanchao Qi +4
Pretrained language models (PLMs) perform poorly under adversarial attacks. To improve the adversarial robustness, adversarial data augmentation (ADA) has been widely adopted to co…