Arabzadeh, N., Huo, S., Mehta, N., Wu, Q., Wang, C., Awadallah, A., … Kiseleva, J. (2024). Assessing and Verifying Task Utility in LLM-Powered Applications ArXiv, abs/2405.02178. https://doi.org/10.48550/ARXIV.2405.02178
References
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2024
Arabzadeh, N., & Clarke, C. (2024). Fr\ echet Distance for Offline Evaluation of Information Retrieval Systems With Sparse Labels Presented at the Fr\ Echet Distance for Offline Evaluation of Information Retrieval Systems With Sparse Labels conference. Retrieved from https://aclanthology.org/2024.eacl-long.26
Arabzadeh, N., Golzadeh, K., Risi, C., Clarke, C., & Zhao, J. (2024). KnowFIRES: A Knowledge-Graph Framework for Interpreting Retrieved Entities From Search Presented at the FIRES: A Knowledge-Graph Framework for Interpreting Retrieved Entities From Search conference. https://doi.org/10.1007/978-3-031-56069-9_15
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
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
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
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
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
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