39 citations · 231 across the 43 of their papers we have counts for
27 papers · 1 filter
SurveyAgent-HKA: A multi-agent framework for scientific survey generation with LLMs and human knowledge augmentation
Tong Bao, Mir Tafseer Nayeem, Yi Zhao +2
Automatic scientific survey generation has become an important task in scientific document processing. The common approach of retrieving literature from a single source (e.g., arXi…
More Computational Resources Do Not Ensure Higher Scholarly Impact: Evidence from Leading NLP Conference Papers
Shuai Chen, Tong Bao, Jitong Peng +1
Computational resources are increasingly central to NLP research, but how closely reported GPU capability aligns with scholarly impact remains unclear. We analyze 13,921 ACL, EMNLP…
Enhancing Scientific Named Entity Recognition via Large Language Models: A Type-driven Multi-task Learning Approach
Tong Bao, Yi Zhao, Heng Zhang +1
Scientific named entity recognition (SciNER) plays a crucial role in information extraction and knowledge discovery from scientific texts. Recently, large language models (LLMs) ha…
Leveraging Human Reading Behavior for Keyphrase Extraction: A Webcam-based Eye-tracking Corpus
Chengzhi Zhang, Xinyi Yan, Wenqi Yu
Purpose: Keyphrases are statistically and semantically important textual units that can also attract readers' attention during comprehension. However, existing keyphrase extraction…
Building a Multimodal Dataset of Academic Paper for Keyword Extraction
Jingyu Zhang, Xinyi Yan, Yi Xiang +2
Up to this point, keyword extraction task typically relies solely on textual data. Neglecting visual details and audio features from image and audio modalities leads to deficiencie…
Exploring the relationship between team institutional composition and novelty in academic papers based on fine-grained knowledge entities
Ziling Chen, Chengzhi Zhang, Heng Zhang +3
The composition of author teams is an important factor influencing the novelty of academic papers. However, existing studies have paid limited attention to the role of institutiona…
Exploring Motivations for Algorithm Mention in the Domain of Natural Language Processing: A Deep Learning Approach
Yuzhuo Wang, Yi Xiang, Chengzhi Zhang
With the rise of data-intensive science, algorithms have become central to scientific research. In academic papers, algorithms are mentioned for different purposes, such as describ…
Revealing the Technology Development of Natural Language Processing: A Scientific Entity-Centric Perspective
Heng Zhang, Chengzhi Zhang, Yuzhuo Wang
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 d…
Utilizing Cognitive Signals Generated during Human Reading to Enhance Keyphrase Extraction from Microblogs
Xinyi Yan, Yingyi Zhang, Chengzhi Zhang
Microblogging platforms generate massive amounts of short, noisy, and dispersed user content, making automatic keyphrase extraction (AKE) an important but challenging task. Prior s…
Extracting Problem and Method Sentence from Scientific Papers: A Context-enhanced Transformer Using Formulaic Expression Desensitization
Yingyi Zhang, Chengzhi Zhang
Billions of scientific papers lead to the need to identify essential parts from the massive text. Scientific research is an activity from putting forward problems to using methods.…
Automatic Generation of Highlights for Academic Paper Via Prompt-based Learning
Yi Xiang, Chengzhi Zhang, Heng Zhang
Highlights provide a concise summary of the main contributions of an academic paper and help readers quickly understand its focus. However, many journals do not provide highlights,…
Aspect-Based Sentiment Evolution and its Correlation with Review Rounds in Multi-Round Peer Reviews: A Deep Learning Approach
Ruxue Hana, Haomin Zhoua, Jiangtao Zhong +1
Mining sentiment information from the textual content of peer review comments offers valuable insights into the scientific evaluation process. However, previous studies are often c…
Which Review Aspect Has a Greater Impact on the Duration of Open Peer Review in Multiple Rounds? -- Evidence from Nature Communications
Haomin Zhou, Ruxue Han, Jiangtao Zhong +1
Purpose: Peer review is essential to scientific publishing, but increasing submission volumes have placed growing pressure on reviewers and editors. This study examines the relatio…
Which Sections of a Research Paper Best Reveal Its Research Methods? Evidence from Library and Information Science
Qiuyu Fang, Jiayi Hao, Chengzhi Zhang
Research methods are essential carriers of knowledge contribution in academic papers. Automatic multi-label classification of research methods can support knowledge services such a…
Detection and Interpretability Analysis of Quotation Errors by Large Language Models
Bei Huang, Yingyi Zhang, Shenghao Huang +1
Purpose - Quotation error refers to the inconsistency between cited information and its original source. This phenomenon leads to a series of negative impacts, such as misinterpret…
Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI
Wenqing Wu, Chengzhi Zhang, Yi Zhao +1
With the rapid advancement of Large Language Models (LLMs), the academic community has faced unprecedented disruptions, particularly in the realm of academic communication. The pri…
NovBench: Evaluating Large Language Models on Academic Paper Novelty Assessment
Wenqing Wu, Yi Zhao, Yuzhuo Wang +4
Novelty is a core requirement in academic publishing and a central focus of peer review, yet the growing volume of submissions has placed increasing pressure on human reviewers. Wh…
Quantifying the Knowledge Proximity Between Academic and Industry Research: An Entity and Semantic Perspective
Hongye Zhao, Yi Zhao, Chengzhi Zhang
The academia and industry are characterized by a reciprocal shaping and dynamic feedback mechanism. Despite distinct institutional logics, they have adapted closely in collaborativ…
The Effect of Gender Diversity on Scientific Team Impact: A Team Roles Perspective
Yi Zhao, Yongjun Zhu, Donghun Kim +4
The influence of gender diversity on the success of scientific teams is of great interest to academia. However, prior findings remain inconsistent, and most studies operationalize…
Automated Generation of Research Workflows from Academic Papers: A Full-text Mining Framework
Heng Zhang, Chengzhi Zhang
The automated generation of research workflows is essential for improving the reproducibility of research and accelerating the paradigm of "AI for Science". However, existing metho…
SciNLP: A Domain-Specific Benchmark for Full-Text Scientific Entity and Relation Extraction in NLP
Decheng Duan, Yingyi Zhang, Jitong Peng +1
Structured information extraction from scientific literature is crucial for capturing core concepts and emerging trends in specialized fields. While existing datasets aid model dev…
SurveyGen: Quality-Aware Scientific Survey Generation with Large Language Models
Tong Bao, Mir Tafseer Nayeem, Davood Rafiei +1
Automatic survey generation has emerged as a key task in scientific document processing. While large language models (LLMs) have shown promise in generating survey texts, the lack…
SC4ANM: Identifying Optimal Section Combinations for Automated Novelty Prediction in Academic Papers
Wenqing Wu, Chengzhi Zhang, Tong Bao +1
Novelty is a core component of academic papers, and there are multiple perspectives on the assessment of novelty. Existing methods often focus on word or entity combinations, which…
Are the confidence scores of reviewers consistent with the review content? Evidence from top conference proceedings in AI
Wenqing Wu, Haixu Xi, Chengzhi Zhang
Peer review is vital in academia for evaluating research quality. Top AI conferences use reviewer confidence scores to ensure review reliability, but existing studies lack fine-gra…