AI evidence extraction

Hallucinated citations produced by generative artificial intelligence may constitute research misconduct when citations function as data in scholarly papers

David B Resnik, Mohammad Hosseini · Accountability in Research · 2026

AI-generated evidence extraction, verified across multiple analytical personas. Not a substitute for the peer-reviewed original.

10/10

Relevance

1/4

Quality (LMQS)

Evidence

Citations

45.11

FWCI

Top 10%

Impact

This is an AI analysis. Read the peer-reviewed original at the publisher: https://doi.org/10.1080/08989621.2026.2645390

Methodology & findings

Study design

Conceptual/theoretical analysis and argumentation based on review of existing regulations and scholarly practices.

Main result

The authors argue that "GenAI hallucinated citations might qualify as a provable instance of research misconduct under the U.S. federal regulations when a) the researcher uses a GenAI tool to produce hallucinated (i.e., nonexistent) citations for a research document; b) the citations function as data because they directly support research findings, as in, for example, review articles or bibliometric studies; and c) the researcher demonstrates indifference to the risk of fabrication of the data (i.e. citations) because they did not check the GenAI's output for veracity and accuracy."

Research paradigm

Interpretive/argumentative; conceptual analysis of research ethics and AI-related misconduct

Author conclusions

The authors conclude that "Recognizing that GenAI hallucinated citations could be regarded as research misconduct in certain cases will hopefully encourage researchers to take this problem more seriously than they do now. In partnership with scientific institutions, funders and professional societies, the scholarly community should work on establishing, promoting, and enforcing standards for responsible use of AI in research, including standards pertaining to citation practices."

Open questions raised

The paper identifies the need for establishing, promoting, and enforcing standards for responsible use of AI in research, particularly regarding citation practices, suggesting this as an area requiring future development by the scholarly community in partnership with institutions, funders, and professional societies.
The paper identifies the need for establishing, promoting, and enforcing standards for responsible use of AI in research, particularly regarding citation practices, in partnership with scientific institutions, funders, and professional societies.
The authors identify the need for the scholarly community to establish, promote, and enforce standards for responsible use of AI in research, particularly regarding citation practices. They call for collaborative action among scientific institutions, funders, and professional societies.

Data: not_statedCode: not_statedExtracted from: pdfAgreement 80%

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