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20192022
most citedStructural block driven - enhanced convolutional neural representation for relation extraction

25 citations · 44 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.CL20241 cited

2M-NER: Contrastive Learning for Multilingual and Multimodal NER with Language and Modal Fusion

Dongsheng Wang, Xiaoqin Feng, Zeming Liu +1

Named entity recognition (NER) is a fundamental task in natural language processing that involves identifying and classifying entities in sentences into pre-defined types. It plays…

cs.CL20244 cited

Large Language Models as Financial Data Annotators: A Study on Effectiveness and Efficiency

Toyin Aguda, Suchetha Siddagangappa, Elena Kochkina +4

Collecting labeled datasets in finance is challenging due to scarcity of domain experts and higher cost of employing them. While Large Language Models (LLMs) have demonstrated rema…

cs.CL202125 cited

Structural block driven - enhanced convolutional neural representation for relation extraction

Dongsheng Wang, Prayag Tiwari, Sahil Garg +2

In this paper, we propose a novel lightweight relation extraction approach of structural block driven - convolutional neural learning. Specifically, we detect the essential sequent…

cs.CL2020

Multi-Head Self-Attention with Role-Guided Masks

Dongsheng Wang, Casper Hansen, Lucas Chaves Lima +4

The state of the art in learning meaningful semantic representations of words is the Transformer model and its attention mechanisms. Simply put, the attention mechanisms learn to a…

cs.CL20199 cited

MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims

Isabelle Augenstein, Christina Lioma, Dongsheng Wang +4

We contribute the largest publicly available dataset of naturally occurring factual claims for the purpose of automatic claim verification. It is collected from 26 fact checking we…

cs.CL2019

Contextual Compositionality Detection with External Knowledge Bases andWord Embeddings

Dongsheng Wang, Quichi Li, Lucas Chaves Lima +2

When the meaning of a phrase cannot be inferred from the individual meanings of its words (e.g., hot dog), that phrase is said to be non-compositional. Automatic compositionality d…