Re-examining lexical and semantic attention: Dual-view graph convolutions enhanced BERT for academic paper rating
Automatically assessing academic papers has enormous potential to reduce peer-review
burden and individual bias. Existing studies strive for building sophisticated deep neural …
burden and individual bias. Existing studies strive for building sophisticated deep neural …
Longitudinal citation prediction using temporal graph neural networks
Citation count prediction is the task of predicting the number of citations a paper has gained
after a period of time. Prior work viewed this as a static prediction task. As papers and their …
after a period of time. Prior work viewed this as a static prediction task. As papers and their …
[HTML][HTML] Content-based quality evaluation of scientific papers using coarse feature and knowledge entity network
Pre-evaluating scientific paper quality aids in alleviating peer review pressure and fostering
scientific advancement. Although prior studies have identified numerous quality-related …
scientific advancement. Although prior studies have identified numerous quality-related …
SChuBERT: Scholarly document chunks with BERT-encoding boost citation count prediction
T van Dongen, GMB Wenniger… - arXiv preprint arXiv …, 2020 - arxiv.org
Predicting the number of citations of scholarly documents is an upcoming task in scholarly
document processing. Besides the intrinsic merit of this information, it also has a wider use …
document processing. Besides the intrinsic merit of this information, it also has a wider use …
Exploiting labeled and unlabeled data via transformer fine-tuning for peer-review score prediction
Abstract Automatic Peer-review Aspect Score Prediction (PASP) of academic papers can be
a helpful assistant tool for both reviewers and authors. Most existing works on PASP utilize …
a helpful assistant tool for both reviewers and authors. Most existing works on PASP utilize …
The Quality Assist: A Technology-Assisted Peer Review Based on Citation Functions to Predict the Paper Quality
S Basuki, M Tsuchiya - IEEE Access, 2022 - ieeexplore.ieee.org
This study aims to develop a prediction model for paper quality assessment to support
technology-assisted peer review. The prediction technique is intended to reduce the review …
technology-assisted peer review. The prediction technique is intended to reduce the review …
Pretrained Language Model based Web Search Ranking: From Relevance to Satisfaction
Search engine plays a crucial role in satisfying users' diverse information needs. Recently,
Pretrained Language Models (PLMs) based text ranking models have achieved huge …
Pretrained Language Models (PLMs) based text ranking models have achieved huge …
Translating scientific abstracts in the bio-medical domain with structure-aware models
Abstract Machine Translation (MT) technologies have improved in many ways and generate
usable outputs for a growing number of domains and language pairs. Yet, most sentence …
usable outputs for a growing number of domains and language pairs. Yet, most sentence …
Quality prediction of scientific documents using textual and visual content
TA van Dongen - 2021 - fse.studenttheses.ub.rug.nl
In this thesis, multiple methods are proposed to improve upon the task of scholarly document
quality prediction (SDQP). Specifically, the two sub-tasks of accept/reject prediction and …
quality prediction (SDQP). Specifically, the two sub-tasks of accept/reject prediction and …
MultiSChuBERT: Effective Multimodal Fusion for Scholarly Document Quality Prediction
GMB Wenniger, T van Dongen… - arXiv preprint arXiv …, 2023 - arxiv.org
Automatic assessment of the quality of scholarly documents is a difficult task with high
potential impact. Multimodality, in particular the addition of visual information next to text, has …
potential impact. Multimodality, in particular the addition of visual information next to text, has …