GNN 리뷰논문 - ieeexplore.ieee.org/abstract/document/9046288

Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., & Philip, S. Y. (2020). A comprehensive survey on graph neural networks. IEEE transactions on neural networks and learning systems.

 

A Comprehensive Survey on Graph Neural Networks

Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language understanding. The data in these tasks are typically represented in the Euclidea

ieeexplore.ieee.org

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SciCite - arxiv.org/pdf/1904.01608.pdf

Cohan, A., Ammar, W., Van Zuylen, M., & Cady, F. (2019). Structural scaffolds for citation intent classification in scientific publications. arXiv preprint arXiv:1904.01608.

 

Structural Scaffolds for Citation Intent Classification in Scientific Publications

Identifying the intent of a citation in scientific papers (e.g., background information, use of methods, comparing results) is critical for machine reading of individual publications and automated analysis of the scientific literature. We propose structura

arxiv.org

Github - github.com/allenai/scicite

 

allenai/scicite

Repository for NAACL 2019 paper on Citation Intent prediction - allenai/scicite

github.com

Tensorflow SciCite Dataset - www.tensorflow.org/datasets/catalog/scicite

 

scicite  |  TensorFlow Datasets

학술 논문에서 인용 의도를 분류하기위한 데이터 세트입니다. 각 Json 객체의 기본 인용 의도 레이블은 레이블 키로 지정되고 인용 컨텍스트는 컨텍스트 키로 지정됩니다. 예 : { 'string': 'chacma 개

www.tensorflow.org

 

 

 

 

 

인용의도 선행연구 - transacl.org/ojs/index.php/tacl/article/view/1266

Jurgens, D., Kumar, S., Hoover, R., McFarland, D., & Jurafsky, D. (2018). Measuring the evolution of a scientific field through citation frames. Transactions of the Association for Computational Linguistics, 6, 391-406.

 

Measuring the Evolution of a Scientific Field through Citation Frames | Jurgens | Transactions of the Association for Computatio

Abstract Citations have long been used to characterize the state of a scientific field and to identify influential works. However, writers use citations for different purposes, and this varied purpose influences uptake by future scholars.  Unfortunately,

transacl.org

 

 

 

 

Paper With Code / SciCite Ranking - SciBERT 1위

paperswithcode.com/sota/sentence-classification-on-scicite

 

Papers with Code - SciCite Benchmark (Sentence Classification)

The current state-of-the-art on SciCite is SciBERT. See a full comparison of 6 papers with code.

paperswithcode.com

 

 

 

SciBert - arxiv.org/abs/1903.10676

Beltagy, I., Lo, K., & Cohan, A. (2019). SciBERT: A pretrained language model for scientific text. arXiv preprint arXiv:1903.10676.

 

SciBERT: A Pretrained Language Model for Scientific Text

Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive. We release SciBERT, a pretrained language model based on BERT (Devlin et al., 2018) to address the lack of high-quality, large-scale labeled scientifi

arxiv.org

Github - github.com/allenai/scibert

 

allenai/scibert

A BERT model for scientific text. Contribute to allenai/scibert development by creating an account on GitHub.

github.com

 

 

 

ImpactCite - arxiv.org/abs/2005.06611

Mercier, D., Rizvi, S. T. R., Rajashekar, V., Dengel, A., & Ahmed, S. (2020). ImpactCite: An XLNet-based method for Citation Impact Analysis. arXiv preprint arXiv:2005.06611.

 

ImpactCite: An XLNet-based method for Citation Impact Analysis

Citations play a vital role in understanding the impact of scientific literature. Generally, citations are analyzed quantitatively whereas qualitative analysis of citations can reveal deeper insights into the impact of a scientific artifact in the communit

arxiv.org

Github - github.com/DominiqueMercier/ImpactCite

 

DominiqueMercier/ImpactCite

ImpactCite: A XLNet-based Solution Enabling Qualitative CitationImpact Analysis Utilizing Sentiment and Intent - DominiqueMercier/ImpactCite

github.com

 

 

 

기타  / 3C 분류 성능평가 - oro.open.ac.uk/73290/

Kunnath, S. N., Pride, D., Gyawali, B., & Knoth, P. (2020). Overview of the 2020 wosp 3c citation context classification task. In Proceedings of the 8th International Workshop on Mining Scientific Publications (pp. 75-83). Association for Computational Linguistics.

 

Overview of the 2020 WOSP 3C Citation Context Classification Task - Open Research Online

Kunnath, Suchetha N.; Pride, David; Gyawali, Bikash and Knoth, Petr (2020). Overview of the 2020 WOSP 3C Citation Context Classification Task. In: Proceedings of the 8th International Workshop on Mining Scientific Publications, Association for Computationa

oro.open.ac.uk

 

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