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
Sharifymoghaddam, S., Upadhyay, S., Chen, W., & Lin, J. (2024). UniRAG: Universal Retrieval Augmentation for Multi-Modal Large Language Models ArXiv, abs/2405.10311. https://doi.org/10.48550/ARXIV.2405.10311
Arabzadeh, N., & Clarke, C. (2024). A Comparison of Methods for Evaluating Generative IR ArXiv, abs/2404.04044. https://doi.org/10.48550/ARXIV.2404.04044
Arabzadeh, N., Kiseleva, J., Wu, Q., Wang, C., Awadallah, A., Dibia, V., … Clarke, C. (2024). Towards Better Human-Agent Alignment: Assessing Task Utility in LLM-Powered Applications ArXiv, abs/2402.09015. https://doi.org/10.48550/ARXIV.2402.09015
Usta, A., Liu, C., & Salihoglu, S. (2024). Analysis of Open Government Datasets From a Data Design and Integration Perspective Presented at the Analysis of Open Government Datasets From a Data Design and Integration Perspective conference. https://doi.org/10.48786/EDBT.2024.30
Xian, J., Teofili, T., Pradeep, R., & Lin, J. (2024). Vector Search With OpenAI Embeddings: Lucene Is All You Need Presented at the Vector Search With OpenAI Embeddings: Lucene Is All You Need conference. https://doi.org/10.1145/3616855.3635691
Golzadeh, K., Golab, L., & Szlichta, J. (2024). Explaining Expert Search and Team Formation Systems With ExES ArXiv, abs/2405.12881. https://doi.org/10.48550/ARXIV.2405.12881
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
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
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