# HalluCitation Matters: Revealing the Impact of Hallucinated References with 300 Hallucinated Papers in ACL Conferences

arXiv: https://arxiv.org/abs/2601.18724 · HTML: https://mlsanity.com/paper/2601.18724/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 344 references that are in the map.
- First posted on arXiv 26 Jan 2026.

## Builds on (most cited first, 17 of 17)

- [The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search](https://mlsanity.com/paper/2504.08066/) (2025)
- [MinerU: An Open-Source Solution for Precise Document Content Extraction](https://mlsanity.com/paper/2409.18839/) (2024)
- [DeepSeek-OCR: Contexts Optical Compression](https://mlsanity.com/paper/2510.18234/) (2025)
- [OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts](https://mlsanity.com/paper/2205.01833/) (2022)
- [Deep Research Agents: A Systematic Examination And Roadmap](https://mlsanity.com/paper/2506.18096/) (2025)
- [Benchmarking Batch Deep Reinforcement Learning Algorithms](https://mlsanity.com/paper/1910.01708/) (2019)
- [AI-Researcher: Autonomous Scientific Innovation](https://mlsanity.com/paper/2505.18705/) (2025)
- [PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model](https://mlsanity.com/paper/2510.14528/) (2025)
- [OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs](https://mlsanity.com/paper/2411.14199/) (2024)
- [From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery](https://mlsanity.com/paper/2508.14111/) (2025)
- [AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://mlsanity.com/paper/2507.01903/) (2025)
- [Deep Research: A Systematic Survey](https://mlsanity.com/paper/2512.02038/) (2025)
- [Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows](https://mlsanity.com/paper/2512.16969/) (2025)
- [OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists](https://mlsanity.com/paper/2511.16931/) (2025)
- [A Systematic Evaluation of Large Language Models for Natural Language Generation Tasks](https://mlsanity.com/paper/2405.10251/) (2024)
- [Decentralized Picosecond Synchronization for Distributed Wireless Systems](https://mlsanity.com/paper/2405.18384/) (2024)
- [Can MLLMs Detect Phishing? A Comprehensive Security Benchmark Suite Focusing on Dynamic Threats and Multimodal Evaluation in Academic Environments](https://mlsanity.com/paper/2511.15165/) (2025)

## Built on by (most cited first, 19 of 19)

- [CiteAudit: You Cited It, But Did You Read It? A Benchmark for Verifying Scientific References in the LLM Era](https://mlsanity.com/paper/2602.23452/) (2026)
- [GhostCite: A Large-Scale Analysis of Citation Validity in the Age of Large Language Models](https://mlsanity.com/paper/2602.06718/) (2026)
- [LLM hallucinations in the wild: Large-scale evidence from non-existent citations](https://mlsanity.com/paper/2605.07723/) (2026)
- [Detecting and Correcting Reference Hallucinations in Commercial LLMs and Deep Research Agents](https://mlsanity.com/paper/2604.03173/) (2026)
- [Source or It Didn't Happen: A Multi-Agent Framework for Citation Hallucination Detection](https://mlsanity.com/paper/2605.08583/) (2026)
- [BibTeX Citation Errors in Scientific Publishing Agents: Evaluation and Mitigation](https://mlsanity.com/paper/2604.03159/) (2026)
- [HALLMARK: How to Diagnose LLM Citation Verifiers and When to Deploy Them](https://mlsanity.com/paper/2607.18360/) (2026)
- [Beyond Via: Analysis and Estimation of the Impact of Large Language Models in Academic Papers](https://mlsanity.com/paper/2603.25638/) (2026)
- [HalluCiteChecker: A Lightweight Toolkit for Hallucinated Citation Detection and Verification in the Era of AI Scientists](https://mlsanity.com/paper/2604.26835/) (2026)
- [Phantom References: Hallucinated Citations That Survive Peer Review at Top-Tier Conferences](https://mlsanity.com/paper/2607.00738/) (2026)
- [Paper Reconstruction Evaluation: Evaluating Presentation and Hallucination in AI-written Papers](https://mlsanity.com/paper/2604.01128/) (2026)
- [How unique are hallucinated citations offered by generative Artificial Intelligence models?](https://mlsanity.com/paper/2604.16407/) (2026)
- [Toward an Engineering of Science: Rebalancing Generation and Verification in the Age of AI](https://mlsanity.com/paper/2605.10425/) (2026)
- [Does Finetuning with Scientific Data Increase Hallucinations? A Multi-domain Factuality Evaluation of LLMs](https://mlsanity.com/paper/2606.21359/) (2026)
- [Position: Reasoning is a Learnable Rule-Based Process](https://mlsanity.com/paper/2608.12325/) (2026)
- [Is this Citation on Point?](https://mlsanity.com/paper/2608.12571/) (2026)
- [ReCite: Agentic Reasoning for Faithful Citation](https://mlsanity.com/paper/2609.09156/) (2026)
- [ATTRICITE: Training an Open 4B Model for Citation Recovery toward Faithful Attribution](https://mlsanity.com/paper/2609.14248/) (2026)
- [BizSage: A Self-Evolving Multi-Agent Framework for Business Research with Efficient Knowledge Retrieval](https://mlsanity.com/paper/2609.22235/) (2026)

## Abstract (arXiv)

Recently, we have often observed hallucinated citations or references that do not correspond to any existing work in papers under review, preprints, or published papers. Such hallucinated citations pose a serious concern to scientific reliability. When they appear in accepted papers, they may also negatively affect the credibility of conferences. In this study, we refer to hallucinated citations as "HalluCitation" and systematically investigate their prevalence and impact. We analyze all papers published at ACL, NAACL, and EMNLP in 2024 and 2025, including main conference, Findings, and workshop papers. Our analysis reveals that nearly 300 papers contain at least one HalluCitation, most of which were published in 2025. Notably, half of these papers were identified at EMNLP 2025, the most recent conference, indicating that this issue is rapidly increasing. Moreover, more than 100 such papers were accepted as main conference and Findings papers at EMNLP 2025, affecting the credibility.