activity
20192022
most citedLearning Robust Representations for Continual Relation Extraction via Adversarial Class Augmentation

4 citations · 10 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL20224 cited

Learning Robust Representations for Continual Relation Extraction via Adversarial Class Augmentation

Peiyi Wang, Yifan Song, Tianyu Liu +4

Continual relation extraction (CRE) aims to continually learn new relations from a class-incremental data stream. CRE model usually suffers from catastrophic forgetting problem, i.…

cs.CL2022

A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction

Runxin Xu, Peiyi Wang, Tianyu Liu +3

Most previous studies aim at extracting events from a single sentence, while document-level event extraction still remains under-explored. In this paper, we focus on extracting eve…

cs.CL2022

ATP: AMRize Then Parse! Enhancing AMR Parsing with PseudoAMRs

Liang Chen, Peiyi Wang, Runxin Xu +3

As Abstract Meaning Representation (AMR) implicitly involves compound semantic annotations, we hypothesize auxiliary tasks which are semantically or formally related can better enh…

cs.CL20221 cited

SmartSales: Sales Script Extraction and Analysis from Sales Chatlog

Hua Liang, Tianyu Liu, Peiyi Wang +2

In modern sales applications, automatic script extraction and management greatly decrease the need for human labor to collect the winning sales scripts, which largely boost the suc…

cs.CL20222 cited

Incorporating Hierarchy into Text Encoder: a Contrastive Learning Approach for Hierarchical Text Classification

Zihan Wang, Peiyi Wang, Lianzhe Huang +2

Hierarchical text classification is a challenging subtask of multi-label classification due to its complex label hierarchy. Existing methods encode text and label hierarchy separat…

cs.CL20212 cited

Behind the Scenes: An Exploration of Trigger Biases Problem in Few-Shot Event Classification

Peiyi Wang, Runxin Xu, Tianyu Liu +3

Few-Shot Event Classification (FSEC) aims at developing a model for event prediction, which can generalize to new event types with a limited number of annotated data. Existing FSEC…