activity
20192023
most citedA Survey on In-context Learning

257 citations · 379 across the 36 of their papers we have counts for

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Showing 2022 · cs.CLShow all

9 papers · 2 filters

cs.CL2022★ 1 cited

Query Your Model with Definitions in FrameNet: An Effective Method for Frame Semantic Role Labeling

Ce Zheng, Yiming Wang, Baobao Chang

Frame Semantic Role Labeling (FSRL) identifies arguments and labels them with frame semantic roles defined in FrameNet. Previous researches tend to divide FSRL into argument identi…

cs.CL2022

A Two-Stage Method for Chinese AMR Parsing

Liang Chen, Bofei Gao, Baobao Chang

In this paper, we provide a detailed description of our system at CAMRP-2022 evaluation. We firstly propose a two-stage method to conduct Chinese AMR Parsing with alignment generat…

cs.CL2022★ 2 cited

SCL-RAI: Span-based Contrastive Learning with Retrieval Augmented Inference for Unlabeled Entity Problem in NER

Shuzheng Si, Shuang Zeng, Jiaxing Lin +1

Named Entity Recognition is the task to locate and classify the entities in the text. However, Unlabeled Entity Problem in NER datasets seriously hinders the improvement of NER per…

cs.CL2022★ 13 cited

A Double-Graph Based Framework for Frame Semantic Parsing

Ce Zheng, Xudong Chen, Runxin Xu +1

Frame semantic parsing is a fundamental NLP task, which consists of three subtasks: frame identification, argument identification and role classification. Most previous studies ten…

cs.CL2022★ 3 cited

Robust Fine-tuning via Perturbation and Interpolation from In-batch Instances

Shoujie Tong, Qingxiu Dong, Damai Dai +4

Fine-tuning pretrained language models (PLMs) on downstream tasks has become common practice in natural language processing. However, most of the PLMs are vulnerable, e.g., they ar…

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…