Scholarly knowledge graphs through structuring scholarly communication: a review
The necessity for scholarly knowledge mining and management has grown significantly as
academic literature and its linkages to authors produce enormously. Information extraction …
academic literature and its linkages to authors produce enormously. Information extraction …
Revealing the technology development of natural language processing: A Scientific entity-centric perspective
H Zhang, C Zhang, Y Wang - Information Processing & Management, 2024 - Elsevier
Most studies on technology development have been conducted from a thematic perspective,
but the topics are coarse-grained and insufficient to accurately represent technology. The …
but the topics are coarse-grained and insufficient to accurately represent technology. The …
Transformers go for the LOLs: Generating (humourous) titles from scientific abstracts end-to-end
We consider the end-to-end abstract-to-title generation problem, exploring seven recent
transformer based models (including ChatGPT) fine-tuned on more than 30k abstract-title …
transformer based models (including ChatGPT) fine-tuned on more than 30k abstract-title …
[PDF][PDF] End-to-end construction of NLP knowledge graph
This paper studies the end-to-end construction of an NLP Knowledge Graph (KG) from
scientific papers. We focus on extracting four types of relations: evaluatedOn between tasks …
scientific papers. We focus on extracting four types of relations: evaluatedOn between tasks …
Automated mining of leaderboards for empirical ai research
With the rapid growth of research publications, empowering scientists to keep an oversight
over scientific progress is of paramount importance. In this regard, the leaderboards facet of …
over scientific progress is of paramount importance. In this regard, the leaderboards facet of …
Zero-shot entailment of leaderboards for empirical ai research
We present a large-scale empirical investigation of the zero-shot learning phenomena in a
specific recognizing textual entailment (RTE) task category, ie, the automated mining of …
specific recognizing textual entailment (RTE) task category, ie, the automated mining of …
[PDF][PDF] Discovering data sets through machine learning: An ensemble approach to uncovering the prevalence of government-funded data sets
R Hausen, H Azarbonyad - Harvard Data Science Review, 2024 - assets.pubpub.org
The prevalence of government-funded dataset usage has yet to be comprehensively tracked
and understood. The lack of a standardized citation methodology has thus far prevented the …
and understood. The lack of a standardized citation methodology has thus far prevented the …
Personal research knowledge graphs
P Chakraborty, S Dutta, DK Sanyal - Companion Proceedings of the …, 2022 - dl.acm.org
Maintaining research-related information in an organized manner can be challenging for a
researcher. In this paper, we envision personal research knowledge graphs (PRKGs) as a …
researcher. In this paper, we envision personal research knowledge graphs (PRKGs) as a …
Aclm: A selective-denoising based generative data augmentation approach for low-resource complex ner
Complex Named Entity Recognition (NER) is the task of detecting linguistically complex
named entities in low-context text. In this paper, we present ACLM Attention-map aware …
named entities in low-context text. In this paper, we present ACLM Attention-map aware …
Named entity recognition as structured span prediction
Abstract Named Entity Recognition (NER) is an important task in Natural Language
Processing with applications in many domains. While the dominant paradigm of NER is …
Processing with applications in many domains. While the dominant paradigm of NER is …