most citedKgPLM: Knowledge-guided Language Model Pre-training via Generative and Discriminative Learning

11 citations · 34 across the 6 of their papers we have counts for

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cs.CL20215 cited

UniDS: A Unified Dialogue System for Chit-Chat and Task-oriented Dialogues

Xinyan Zhao, Bin He, Yasheng Wang +6

With the advances in deep learning, tremendous progress has been made with chit-chat dialogue systems and task-oriented dialogue systems. However, these two systems are often tackl…

cs.CL2021

Benchmarking Commonsense Knowledge Base Population with an Effective Evaluation Dataset

Tianqing Fang, Weiqi Wang, Sehyun Choi +4

Reasoning over commonsense knowledge bases (CSKB) whose elements are in the form of free-text is an important yet hard task in NLP. While CSKB completion only fills the missing lin…

cs.CL202111 cited

Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models

Wenkai Yang, Lei Li, Zhiyuan Zhang +3

Recent studies have revealed a security threat to natural language processing (NLP) models, called the Backdoor Attack. Victim models can maintain competitive performance on clean…

cs.CL20216 cited

DISCOS: Bridging the Gap between Discourse Knowledge and Commonsense Knowledge

Tianqing Fang, Hongming Zhang, Weiqi Wang +2

Commonsense knowledge is crucial for artificial intelligence systems to understand natural language. Previous commonsense knowledge acquisition approaches typically rely on human a…

cs.CL20201 cited

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…

cs.CL202011 cited

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…