← Search

Jianmin Yao

7 accepted papers

2025

REAR: Reinforced Reasoning Optimization for Event Argument Extraction with Relation-Aware Support

EMNLP 2025

Event argument extraction aims to identify event arguments and classify their roles within events, whereas relation extraction classifies semantic relationships between entities. Existing methods typically design task-specific models for EAE, which restricts the integration of relation-level semanti

Cited by 0SourcePDFScholar
2024

Demonstration Retrieval-Augmented Generative Event Argument Extraction

COLING 2024main

We tackle Event Argument Extraction (EAE) in the manner of template-based generation. Based on our exploration of generative EAE, it suffers from several issues, such as multiple arguments of one role, generating words out of context and inconsistency with prescribed format. We attribute it to the w…

Cited by 2SourcePDFScholar
2024

Word-level Commonsense Knowledge Selection for Event Detection

COLING 2024main

Event Detection (ED) is a task of automatically extracting multi-class trigger words. The understanding of word sense is crucial for ED. In this paper, we utilize context-specific commonsense knowledge to strengthen word sense modeling. Specifically, we leverage a Context-specific Knowledge Selector…

2023

Smart “Chef”: Verifying the Effect of Role-based Paraphrasing for Aspect Term Extraction

EMNLP 2023short findings

We tackle Aspect Term Extraction (ATE), a task of automatically extracting aspect terms from sentences. The current Pretrained Language Model (PLM) based extractors have achieved significant improvements. They primarily benefit from context-aware encoding. However, a considerable number of sentences…

Cited by 0SourceScholar
2022

Taking Actions Separately: A Bidirectionally-Adaptive Transfer Learning Method for Low-Resource Neural Machine Translation

COLING 2022main

Training Neural Machine Translation (NMT) models suffers from sparse parallel data, in the infrequent translation scenarios towards low-resource source languages. The existing solutions primarily concentrate on the utilization of Parent-Child (PC) transfer learning. It transfers well-trained NMT mod…

Cited by 7SourcePDFScholar
2022

Unregulated Chinese-to-English Data Expansion Does NOT Work for Neural Event Detection

COLING 2022main

We leverage cross-language data expansion and retraining to enhance neural Event Detection (abbr., ED) on English ACE corpus. Machine translation is utilized for expanding English training set of ED from that of Chinese. However, experimental results illustrate that such strategy actually results in…

Cited by 1SourcePDFScholar