370 citations · 490 across the 11 of their papers we have counts for
5 papers · 1 filter
Document-level Relation Extraction as Semantic Segmentation
Ningyu Zhang, Xiang Chen, Xin Xie +6
Document-level relation extraction aims to extract relations among multiple entity pairs from a document. Previously proposed graph-based or transformer-based models utilize the en…
KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction
Xiang Chen, Ningyu Zhang, Xin Xie +6
Recently, prompt-tuning has achieved promising results for specific few-shot classification tasks. The core idea of prompt-tuning is to insert text pieces (i.e., templates) into th…
Disentangled Contrastive Learning for Learning Robust Textual Representations
Xiang Chen, Xin Xie, Zhen Bi +4
Although the self-supervised pre-training of transformer models has resulted in the revolutionizing of natural language processing (NLP) applications and the achievement of state-o…
Normal vs. Adversarial: Salience-based Analysis of Adversarial Samples for Relation Extraction
Luoqiu Li, Xiang Chen, Zhen Bi +6
Recent neural-based relation extraction approaches, though achieving promising improvement on benchmark datasets, have reported their vulnerability towards adversarial attacks. Thu…
ZJUKLAB at SemEval-2021 Task 4: Negative Augmentation with Language Model for Reading Comprehension of Abstract Meaning
Xin Xie, Xiangnan Chen, Xiang Chen +4
This paper presents our systems for the three Subtasks of SemEval Task4: Reading Comprehension of Abstract Meaning (ReCAM). We explain the algorithms used to learn our models and t…