Reference author: Jimmy Lin

Lin, S.-C., Asai, A., Li, M., Oguz, B., Lin, J., Mehdad, Y., … Chen, X. (2023). How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval Presented at the How to Train Your Dragon: Diverse Augmentation Towards Generalizable Dense Retrieval conference. Retrieved from https://aclanthology.org/2023.findings-emnlp.423

Pradeep, R., Hui, K., Gupta, J., Lelkes, A. am D., Zhuang, H., Lin, J., … Tran, V. Q. (2023). How Does Generative Retrieval Scale to Millions of Passages? Presented at the How Does Generative Retrieval Scale to Millions of Passages? conference. Retrieved from https://aclanthology.org/2023.emnlp-main.83

Oladipo, A., Adeyemi, M., Ahia, O., Owodunni, A. T., Ogundepo, O., Adelani, D. I., & Lin, J. (2023). Better Quality Pre-Training Data and T5 Models for African Languages Presented at the Better Quality Pre-Training Data and T5 Models for African Languages conference. Retrieved from https://aclanthology.org/2023.emnlp-main.11

Akiki, C., Ogundepo, O., Piktus, A., Zhang, X., Oladipo, A., Lin, J., & Potthast, M. (2023). Spacerini: Plug-and-Play Search Engines With Pyserini and Hugging Face Presented at the Spacerini: Plug-and-Play Search Engines With Pyserini and Hugging Face conference. Retrieved from https://aclanthology.org/2023.emnlp-demo.12

Tang, R., Zhang, X., Lin, J., & Türe, F. (2023). What Do Llamas Really Think? Revealing Preference Biases in Language Model Representations ArXiv, abs/2311.18812. https://doi.org/10.48550/ARXIV.2311.18812

Chen, H., Lassance, C., & Lin, J. (2023). End-to-End Retrieval With Learned Dense and Sparse Representations Using Lucene ArXiv, abs/2311.18503. https://doi.org/10.48550/ARXIV.2311.18503

Li, M., Zhuang, H., Hui, K., Qin, Z., Lin, J., Jagerman, R., … Bendersky, M. (2023). Generate, Filter, and Fuse: Query Expansion via Multi-Step Keyword Generation for Zero-Shot Neural Rankers ArXiv, abs/2311.09175. https://doi.org/10.48550/ARXIV.2311.09175

Thakur, N., Ni, J., Abrego, G. H. andez \, Wieting, J., Lin, J., & Cer, D. (2023). Leveraging LLMs for Synthesizing Training Data Across Many Languages In Multilingual Dense Retrieval ArXiv, abs/2311.05800. https://doi.org/10.48550/ARXIV.2311.05800

Ma, X., Fun, H., Yin, X., Mallia, A., & Lin, J. (2023). Enhancing Sparse Retrieval via Unsupervised Learning Presented at the Enhancing Sparse Retrieval via Unsupervised Learning conference. https://doi.org/10.1145/3624918.3625334

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