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Found 18 papers, 8 papers with code
Overview of the First Shared Task on Multi Perspective Scientific Document Summarization (MuP)
We present the main findings of MuP 2022 shared task, the first shared task on multi-perspective scientific document summarization.
Team Innovators at SemEval-2022 for Task 8: Multi-Task Training with Hyperpartisan and Semantic Relation for Multi-Lingual News Article Similarity
This work represents the system proposed by team Innovators for SemEval 2022 Task 8: Multilingual News Article Similarity.
Overview of the Third Workshop on Scholarly Document Processing
With the ever-increasing pace of research and high volume of scholarly communication, scholars face a daunting task.
An Extractive-Abstractive Approach for Multi-document Summarization of Scientific Articles for Literature Review
Research in the biomedical domain is con- stantly challenged by its large amount of ever- evolving textual information.
Overview of the First Workshop on Scholarly Document Processing (SDP)
To reach to the broader NLP and AI/ML community, pool distributed efforts and enable shared access to published research, we held the 1st Workshop on Scholarly Document Processing at EMNLP 2020 as a virtual event.
IITP-CUNI@3C: Supervised Approaches for Citation Classification (Task A) and Citation Significance Detection (Task B)
With the rapid growth in research publications, automated solutions for identifying the purpose and influence of citations are becoming very important.
Novelty Detection: A Perspective from Natural Language Processing
In this work, we build upon our earlier investigations for document-level novelty detection and present a comprehensive account of our efforts toward the problem.
ELITR Minuting Corpus: A Novel Dataset for Automatic Minuting from Multi-Party Meetings in English and Czech
Our dataset, AutoMin, consists of 113 (English) and 53 (Czech) meetings, covering more than 160 hours of meeting content.
Argument Mining for Scholarly Document Processing: Taking Stock and Looking Ahead
Argument mining targets structures in natural language related to interpretation and persuasion which are central to scientific communication.
Overview of the Second Workshop on Scholarly Document Processing
With the ever-increasing pace of research and high volume of scholarly communication, scholars face a daunting task.
When Reviewers Lock Horn: Finding Disagreement in Scientific Peer Reviews
To the best of our knowledge, we make the first attempt to identify disagreements among peer reviewers automatically.
RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim Verification
Finally, we carry out two-step stance predictions that first differentiate non-relevant rationales and then identify supporting or refuting rationales for a given claim.
Testing the Generalization of Neural Language Models for COVID-19 Misinformation Detection
We expect that evaluating a broad spectrum of datasets and models will benefit future research in developing misinformation detection systems.
INNOVATORS at SemEval-2021 Task-11: A Dependency Parsing and BERT-based model for Extracting Contribution Knowledge from Scientific Papers
In this work, we describe our system submission to the SemEval 2021 Task 11: NLP Contribution Graph Challenge.
DeepSentiPeer: Harnessing Sentiment in Review Texts to Recommend Peer Review Decisions
However, the peer review texts, which contains rich sentiment information of the reviewer, reflecting his/her overall attitude towards the research in the paper, could be a valuable entity to predict the acceptance or rejection of the manuscript under consideration.
Novelty Goes Deep. A Deep Neural Solution To Document Level Novelty Detection
The proposed method outperforms the existing state-of-the-art on a document-level novelty detection dataset by a margin of ∼5{\%} in terms of accuracy.
TAP-DLND 1.0 : A Corpus for Document Level Novelty Detection
Detecting novelty of an entire document is an Artificial Intelligence (AI) frontier problem that has widespread NLP applications, such as extractive document summarization, tracking development of news events, predicting impact of scholarly articles, etc.
