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English Information

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Authors
# Name
1 Vitória Santos(vit2santoss@gmail.com)
2 Carina Dorneles(dorneles@gmail.com)

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Reference
# Reference
1 Balažević, I., Allen, C., and Hospedales, T. (2019). Multi-relational Poincaré graph embeddings. Advances in Neural Information Processing Systems (NeurIPS).
2 Bommarito, M. and Katz, D. M. (2022). Machine Learning for Law: Text, Cases, and Analytics. Cambridge University Press.
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4 Chami, I., Ying, R., Ré, C., and Leskovec, J. (2019). Hyperbolic graph convolutional neural networks. Advances in Neural Information Processing Systems (NeurIPS).
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8 He, N., Madhu, H., Bui, N., Yang, M., and Ying, R. (2025). Hyperbolic deep learning for foundation models: A survey. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’25).
9 Jurafsky, D. and Martin, J. H. (2023). Speech and Language Processing. Pearson, 3rd edition.
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11 Li, Y., Wang, G., and Yang, Y. (2025). Implicit hypergraph neural networks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
12 Manning, C. D., Raghavan, P., and Schütze, H. (2021). Introduction to Information Retrieval. Cambridge University Press, 2nd edition.
13 Mavromatis, C. and Karypis, G. (2024). Gnn-rag: Graph neural retrieval for large language model reasoning.
14 Nguyen, H.-T. and Satoh, K. (2024). ConsRAG: Minimize LLM Hallucinations in the Legal Domain.
15 Singh, S. (2018). Natural language processing for information extraction.
16 Strogatz, S. H. (2015). Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering. Westview Press, 2nd edition.
17 Tang, Y., Qiu, R., and Huang, Z. (2025). Uqlegalai@coliee2025: Advancing legal case retrieval with large language models and graph neural networks.
18 Tang, Y., Qiu, R., Liu, Y., Li, X., and Huang, Z. (2023). Casegnn: Graph neural networks for legal case retrieval with text-attributed graphs.
19 Tang, Y., Qiu, R., Liu, Y., Li, X., and Huang, Z. (2024a). Casegnn++: Graph contrastive learning for legal case retrieval with graph augmentation.
20 Tang, Y., Qiu, R., Yin, H., Li, X., and Huang, Z. (2024b). Caselink: Inductive graph learning for legal case retrieval.
21 Tifrea, A., Becigneul, G., and Ganea, O. (2021). Hyperbolic deep neural networks: A survey. Journal of Machine Learning Research, 22(169):1–42.
22 Zhang, B., Liang, Y., and Wang, H. (2025). Gfm-rag: Graph foundation model for retrieval augmented generation.
23 Zhang, W., Liu, X., and Wang, Y. (2022). Advances in relation extraction for natural language processing. Computational Linguistics, 48(2):245–268.