Belter, I. K. (2025). Automated citation verification in scientific literature using large language models. https://doi.org/10.5281/zenodo.17770680
Open Access: doi.org · DOI
Despite the importance of accurate citations for scientific literature quality, citation errors persist across scholarly publications. This thesis investigates the potential of zero-shot in-context learning with large language models (LLMs) for automated citation verification, specifically examining how linguistic features of citation statements influence classification performance. An existing dataset of 250 citation-reference pairs was re-annotated to extract syntactic and semantic citation…
Cao, C., Arora, R., Cento, P., Budak, A., Manta, K., Farahani, E., Cecere, M., Selemon, A., Sang, J., Gong, L. X., Kloosterman, R., Jiang, S., Saleh, R., Margalik, D., Lin, J., Jomy, J., Xie, J., Chen, D., Gorla, J., … Bobrovitz, N. (2025). Automation of systematic reviews with large language models. medRxiv. https://doi.org/10.1101/2025.06.13.25329541
Open Access: medrxiv.org · DOI
Abstract Importance Systematic reviews (SRs) inform evidence-based decision making. Yet, many take over a year to complete, are labor intensive, prone to human error, and face reproducibility challenges; thus limiting access to timely and reliable information. Objective To validate a large language model (LLM)-based workflow (otto-SR) to automate three of the most labour intensive tasks in performing SR’s: article screening, data extraction, and risk of bias assessment; and to assess its…
Edelman, B., & Skolnick, J. (2025). Valsci: an open-source, self-hostable literature review utility for automated large-batch scientific claim verification using large language models. BMC Bioinformatics, 26(1), Article 140. https://doi.org/10.1186/s12859-025-06159-4
Open Access: bmcbioinformatics.biomedcentral.com · DOI
BACKGROUND: The exponential growth of scientific publications poses a formidable challenge for researchers seeking to validate emerging hypotheses or synthesize existing evidence. In this paper, we introduce Valsci, an open-source, self-hostable utility that automates large-batch scientific claim verification using any OpenAI-compatible large language model. Valsci unites retrieval-augmented generation with structured bibliometric scoring and chain-of-thought prompting, enabling users to…
Haddaway, N. R., Grainger, M. J., & Gray, C. T. (2022). Citationchaser: A tool for transparent and efficient forward and backward citation chasing in systematic searching. Research Synthesis Methods, 13(4), 533–545. https://doi.org/10.1002/jrsm.1563
Open Access: onlinelibrary.wiley.com · DOI
Systematic searching aims to find all possibly relevant research from multiple sources, the basis for an unbiased and comprehensive evidence base. Along with bibliographic databases, systematic reviewers use a variety of additional methods to minimise procedural bias. Citation chasing exploits connections between research articles to identify relevant records for a review by making use of explicit mentions of one article within another. Citation chasing is a popular supplementary search method…
Tiwari, S. (2026). BiblioAudit: Automated citation integrity & verification system. https://doi.org/10.5281/zenodo.18155557
Open Access: doi.org · DOI
Abstract We present BiblioAudit, an open-source framework designed to automate the verification of bibliographic references in academic manuscripts. By checking metadata across five major research databases, this system addresses the growing prevalence of hallucinated citations and metadata errors. This release serves as the official software implementation accompanying the work.
System Capabilities 5-Engine Verification Matrix The system implements a multi-source validation pipeline that…
Tiwari, S. (2026). BiblioAudit: Automated citation integrity & verification system. https://doi.org/10.5281/zenodo.18155558
Open Access: doi.org · DOI
Abstract We present BiblioAudit, an open-source framework designed to automate the verification of bibliographic references in academic manuscripts. By checking metadata across five major research databases, this system addresses the growing prevalence of hallucinated citations and metadata errors. This release serves as the official software implementation accompanying the work.
Zhang, J., Bai, Y., Lv, X., Gu, W., Liu, D., Zou, M., Cao, S., Hou, L., Dong, Y., Feng, L., & Li, J. (2025). LongCite: Enabling LLMs to generate fine-grained citations in long-context QA. Findings of the Association for Computational Linguistics: ACL 2025, 5098–5122. https://doi.org/10.18653/v1/2025.findings-acl.264
Open Access: aclanthology.org · DOI
Though current long-context large language models (LLMs) have demonstrated impressive capacities in answering various questions based on extensive text, the lack of citations in their responses makes user verification difficult, leading to concerns about their trustworthiness due to the potential hallucinations.In this work, we aim to enable long-context LLMs to generate responses with fine-grained sentence-level citations on the fly, thereby improving their faithfulness and verifiability.We…
References
Belter, I. K. (2025). Automated citation verification in scientific literature using large language models. https://doi.org/10.5281/zenodo.17770680
Cao, C., Arora, R., Cento, P., Budak, A., Manta, K., Farahani, E., Cecere, M., Selemon, A., Sang, J., Gong, L. X., Kloosterman, R., Jiang, S., Saleh, R., Margalik, D., Lin, J., Jomy, J., Xie, J., Chen, D., Gorla, J., … Bobrovitz, N. (2025). Automation of systematic reviews with large language models. medRxiv. https://doi.org/10.1101/2025.06.13.25329541
Edelman, B., & Skolnick, J. (2025). Valsci: an open-source, self-hostable literature review utility for automated large-batch scientific claim verification using large language models. BMC Bioinformatics, 26(1), Article 140. https://doi.org/10.1186/s12859-025-06159-4
Haddaway, N. R., Grainger, M. J., & Gray, C. T. (2022). Citationchaser: A tool for transparent and efficient forward and backward citation chasing in systematic searching. Research Synthesis Methods, 13(4), 533–545. https://doi.org/10.1002/jrsm.1563
Tiwari, S. (2026). BiblioAudit: Automated citation integrity & verification system. https://doi.org/10.5281/zenodo.18155557
Tiwari, S. (2026). BiblioAudit: Automated citation integrity & verification system. https://doi.org/10.5281/zenodo.18155558
Zhang, J., Bai, Y., Lv, X., Gu, W., Liu, D., Zou, M., Cao, S., Hou, L., Dong, Y., Feng, L., & Li, J. (2025). LongCite: Enabling LLMs to generate fine-grained citations in long-context QA. Findings of the Association for Computational Linguistics: ACL 2025, 5098–5122. https://doi.org/10.18653/v1/2025.findings-acl.264