Date: 2026-06-18
Format: APA | Mode: all
Results: 3 validated, 1 suggestions, 1 errors out of 5 total
| # | Code | Similarity | Reference |
|---|---|---|---|
| 1 | SUGGESTION | 78% |
ORIGINAL:
Lewis, P., et al. (2020). Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. NeurIPS 33, 9459–9474. arXiv:2005.11401
FORMATTED (APA):
Ranaldi, L. (2026). Multilingual Retrieval-Augmented Generation for Knowledge-Intensive Question Answering Task. Findings of the Association for Computational Linguistics: EACL 2026, 697-716. https://doi.org/10.18653/v1/2026.findings-eacl.35 ⚠️ Multiple Possible Matches (verify manually): Option 1 (47%): Ranaldi (2026) Multilingual Retrieval-Augmented Generation for Knowledge-Intensive Question Answering Task. https://doi.org/10.18653/v1/2026.findings-eacl.35 Option 2 (44%): Wu (2022) An Efficient Memory-Augmented Transformer for Knowledge-Intensive NLP Tasks. https://doi.org/10.18653/v1/2022.emnlp-main.346 Option 3 (40%): Vinayan Kozhipuram (2025) Retrieval-Augmented Generation vs. Baseline LLMs: A Multi-Metric Evaluation for Knowledge-Intensive Content. https://doi.org/10.3390/info16090766 |
| 2 | 95% |
ORIGINAL:
Gao, Y., et al. (2023). Retrieval-Augmented Generation for Large Language Models: A Survey. arXiv:2312.10997
FORMATTED (APA):
Procko, T., & Ochoa, O. (2024). Graph Retrieval-Augmented Generation for Large Language Models: A Survey. https://doi.org/10.2139/ssrn.4895062 |
|
| 3 | OK | 100% |
ORIGINAL:
Johnson, J., Douze, M., Jégou, H. (2021). Billion-Scale Similarity Search with GPUs. IEEE Trans. Big Data 7(3), 535–547. doi:10.1109/TBDATA.2019.2921572 (FAISS)
FORMATTED (APA):
Johnson, J., Douze, M., & Jegou, H. (2021). Billion-Scale Similarity Search with GPUs. IEEE Transactions on Big Data, 7(3), 535-547. https://doi.org/10.1109/tbdata.2019.2921572 |
| 4 | OK | 84% |
ORIGINAL:
Karpukhin, V., et al. (2020). Dense Passage Retrieval for Open-Domain QA. EMNLP . doi:10.18653/v1/2020.emnlp-main.550
FORMATTED (APA):
Karpukhin, V., Oguz, B., Min, S., Lewis, P., Wu, L., Edunov, S., Chen, D., & Yih, W. (2020). Dense Passage Retrieval for Open-Domain Question Answering. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 6769-6781. https://doi.org/10.18653/v1/2020.emnlp-main.550 |
| 5 | OK | 100% |
ORIGINAL:
Shuster, K., et al. (2021). Retrieval Augmentation Reduces Hallucination in Conversation. Findings of EMNLP . doi:10.18653/v1/2021.findings-emnlp.320
FORMATTED (APA):
Shuster, K., Poff, S., Chen, M., Kiela, D., & Weston, J. (2021). Retrieval Augmentation Reduces Hallucination in Conversation. Findings of the Association for Computational Linguistics: EMNLP 2021, 3784-3803. https://doi.org/10.18653/v1/2021.findings-emnlp.320 |
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