C ite A ssist: A System for Automated Preprint Citation and B ib T e X Generation (2024)

Abstract: We present CiteAssist, a system to automate the generation of BibTeX entries for preprints, streamlining the process of bibliographic annotation. Our system extracts metadata, such as author names, titles, publication dates, and keywords, to create standardized annotations within the document. CiteAssist automatically attaches the BibTeX citation to the end of a PDF and links it on the first page of the document so other researchers gain immediate access to the correct citation of the article. This method promotes platform flexibility by ensuring that annotations remain accessible regardless of the repository used to publish or access the preprint. The annotations remain available even if the preprint is viewed externally to CiteAssist. Additionally, the system adds relevant related papers based on extracted keywords to the preprint, providing researchers with additional publications besides those in related work for further reading. Researchers can enhance their preprints organization and reference management workflows through a free and publicly available web interface.

## introduction a common challenge in academic research is tracing citational information for preprints. many researchers experience a low citational impact because their citational information is not accessible easily together with the preprint. this phenomenon is often evident on platforms like researchgate, where numerous articles are downloaded hundreds of times but receive only a few citations @xcite . this discrepancy between reads and citations highlights a difference in how information is consumed and credited (a pattern also observed in contexts such as social media impressions versus likes) and specifically in citation analysis @xcite @xcite . an imbalance between reading and citing papers can have many reasons: researchers may judge a focal work as irrelevant to them, not exciting, not sound, or simply forgetting. yet, a key reason is the accessibility of citational information @xcite . if citation details are consistent and easily accessible, citations are generally higher @xcite . long review processes and publication timelines can slow scientific progress and hinder researchers from proposing state-of-the-art techniques. thus, preprints are often used in modern scientific research. public available preprints promote the rapid exchange of ideas and results before peer-reviewed publications are available, accelerating the spread of knowledge and driving scientific progress @xcite . with the fast growth in the number of preprints, researchers are faced with an ever-growing sea of scientific information @xcite . the sheer volume of preprints make efficient retrieval challenging. so far, there is no easy way to annotate preprints with citational information. while some repositories allow for archiving preprints (e.g., zenodo, figshare, arxiv), the citation details of a paper are often only available through external infrastructure (e.g., publishers, scholarly search engines). to the best of our knowledge, no publicly available system provides the citation details of a paper within the pdf itself in simple format. furthermore, we lack a common way to add recommended literature on related projects within preprints for further reading about a topic over the scope of related work sections. those could be related ideas from other areas, books, or talks that complement a paper but are not directly discussed in related work. we present citeassist, a system designed to simplify the creation and distribution of citation annotations by automatically generating and appending annotations to the preprint. this is achieved either by generating a new pdf with the annotation or by generating a l a t e x file that can be integrated directly into the source document. citeassist provides researchers with a convenient way to enhance their preprint by directly attaching citation information to it, improving the reference management workflow. these annotations capture metadata such as author names, publication details, and abstracts, enabling researchers to create bibliographic records for their preprints. the system also allows users to add custom metadata (e.g., keywords) to the bibtex annotation. by automating this process, researchers can save time that would otherwise be spent on manual annotation. our system is platform-independent as it incorporates all citation details within the paper. the annotation is attached to the preprint; thus, it can be published at any preprint repository. unlike platform-specific solutions, our system accommodates various sources, making it accessible and useful to researchers in various fields. figure 1 (a) shows the first page containing the button to the bibtex entry and (b) the generated annotation itself. in addition, citeassist suggests related papers at the end of an article to complement a traditional "related work" section. related work sections focus on considering the proposed work and crediting previous ideas. however, they are bound to the researcher's awareness of these works, which may include citation amnesia, i.e., not citing good and relevant work @xcite . citeassist mitigates this issue by suggesting additional literature on poten-tially forgotten or overlooked works. researchers can manually add literature they wish to suggest to readers as additional resources. ## system architecture the system architecture of citeassist consists of a frontend, backend, and database. the frontend handles the user interaction and allows users to upload a pdf file, which is parsed by our method and in the backend with grobid. we merge and display the results to the user for correction, if necessary. furthermore, users can add related papers, either provided by the backend via keyword matching or with a provided doi or arxiv id. the system generates a new pdf or l a t e x file with an attached bibtex annotation and related papers. after user approval, these results are uploaded to the backend, where the pdf is stored locally and metadata forwarded to the database. we refer to appendix a for a more detailed system architecture description. ## preprint annotation workflow this section shows a practical example of how researchers can annotate preprints using citeassist. the workflow begins when a user uploads a preprint in pdf format to the citeassist homepage via a drag-and-drop interface or a file selection dialogue as seen in figure 2 . users are then asked to review (figure 3 ), edit potentially incorrect information, or add other relevant metadata (e.g., keywords). users can select relevant suggested keywords and add new ones if desired. the system enhances the compatibility of these keywords through lemmatization. with refined keywords, the backend searches the database for related preprints and displays these on the frontend for user review and selection, as seen in figure 5 . citeassist compiles this information and generates a bibtex annotation containing the edited metadata and selected related papers (figure 11 ). the compiled annotation is attached at the end of the preprint. on the title page of the uploaded article, it adds a button that links to the annotation at the bottom, as shown in figure 10 . users can download the final annotated pdf version or generate l a t e x files to include it directly in the source document. with user consent, the backend stores the annotated pdfs for future access. users can view these files online, share them with colleagues, or download them again. ## bibtex annotation generation we combine the pdf-lib foot_1 library, grobid, and our custom information extraction method to extract bibtex annotation information. our process can be divided into five steps: 1. pdf parsing: the pdf file is parsed using the pdf-lib library, which allows us to access the document's metadata (e.g., title, author, creation date) if available and saved in the pdf. the combination of pdf-libs metadata extraction, grobid, and our custom metadata extraction function allows us to generate bibtex annotations for preprints shown in figure 1b (a figure outlining the process can be found in figure 9 ). ## integration of related papers the integration of related papers is designed to augment the research experience by providing users with access to literature that, while not directly cited as related work, can indicate the reader to other possible related materials. we use keywordbased searches to retrieve a selection of papers that serve as complementary references, offering broader insights into the subject area without overlapping with the core related work already cited. this task involves the following functionalities: integrating related papers into the annotation enhances the paper by providing users access to related resources that contribute insights, broader the existing related work section and further context to their initial findings, and save researchers time and effort from authors and readers. ## final considerations in this work, we introduced citeassist, a system designed to streamline the creation and distribution of bibtex annotations within preprints. citeassist standardizes the reference management process with the help of automatic generation and integration of annotations, either through a newly generated pdf or directly within a l a t e x source document. a button on the title page linking to the annotation improves the usability and accessibility of the citation information of the paper. our system enhances the usability of preprints by embedding citation details and ensures that the annotations are readily accessible, regardless of the publication repository used. additionally, citeassist offers suggestions for related papers, enriching the scope of resources available to researchers about a given publication. citeassist's development reflects the growing importance of digital tools in academic research. by allowing researchers to easily include their citational information into preprints, we see a direct impact on giving authors proper credit and to be cited correctly with the publication venue as opposed to the preprint server. future enhancements could include recommending similar papers based on semantic similarity and providing a more comprehensive representation of the paper's content.