Azzopardi, L., Clarke, C., Kantor, P. B., Mitra, B., Trippas, J. R., & Ren, Z. (2024). The Search Futures Workshop Presented at the The Search Futures Workshop conference. https://doi.org/10.1007/978-3-031-56069-9_57
References
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2024
Zhuang, S., Ma, X., Koopman, B., Lin, J., & Zuccon, G. (2024). PromptReps: Prompting Large Language Models to Generate Dense And Sparse Representations for Zero-Shot Document Retrieval ArXiv, abs/2404.18424. https://doi.org/10.48550/ARXIV.2404.18424
Khalaji, M., Brown, T., Daudjee, K., & Aksenov, V. (2024). Practical Hardware Transactional vEB Trees Presented at the Practical Hardware Transactional VEB Trees conference. https://doi.org/10.1145/3627535.3638504
Arabzadeh, N., Bigdeli, A., & Clarke, C. (2024). Adapting Standard Retrieval Benchmarks to Evaluate Generated Answers ArXiv, abs/2401.04842. https://doi.org/10.48550/ARXIV.2401.04842
Bonifati, A., Ozsu, T., Tian, Y., Voigt, H., Yu, W., & Zhang, W. (2024). The Future of Graph Analytics Presented at the The Future of Graph Analytics conference. https://doi.org/10.1145/3626246.3658369
Alaofi, M., Arabzadeh, N., Clarke, C., & Sanderson, M. (2024). Generative Information Retrieval Evaluation ArXiv, abs/2404.08137. https://doi.org/10.48550/ARXIV.2404.08137
Arabzadeh, N., Bigdeli, A., & Clarke, C. (2024). Adapting Standard Retrieval Benchmarks to Evaluate Generated Answers Presented at the Adapting Standard Retrieval Benchmarks to Evaluate Generated Answers conference. https://doi.org/10.1007/978-3-031-56060-6_26
Li, M., Chen, X., Holtzman, A., Chen, B., Lin, J., Yih, W.- tau, & Lin, X. V. (2024). Nearest Neighbor Speculative Decoding for LLM Generation and Attribution ArXiv, abs/2405.19325. https://doi.org/10.48550/ARXIV.2405.19325
Pradeep, R., & Lin, J. (2024). Towards Automated End-to-End Health Misinformation Free Search With A Large Language Model Presented at the Automated End-to-End Health Misinformation Free Search With A Large Language Model conference. https://doi.org/10.1007/978-3-031-56066-8_9
Zhang, X., Ogueji, K., Ma, X., & Lin, J. (2024). Toward Best Practices for Training Multilingual Dense Retrieval Models ACM Transactions on Information Systems (TOIS), 42, 1-39. https://doi.org/10.1145/3613447