Hebert, L., Golab, L., Poupart, P., & Cohen, R. (2023). FedFormer: Contextual Federation With Attention in Reinforcement Learning Presented at the FedFormer: Contextual Federation With Attention in Reinforcement Learning conference. https://doi.org/10.5555/3545946.3598716
References
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Pradeep, R., Sharifymoghaddam, S., & Lin, J. (2023). RankVicuna: Zero-Shot Listwise Document Reranking With Open-Source Large Language Models ArXiv, abs/2309.15088. https://doi.org/10.48550/ARXIV.2309.15088
Pradeep, R., Sharifymoghaddam, S., & Lin, J. (2023). RankVicuna: Zero-Shot Listwise Document Reranking With Open-Source Large Language Models ArXiv, abs/2309.15088. https://doi.org/10.48550/ARXIV.2309.15088
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
Yang, J.-H., Lassance, C., de Rezende, R. S., Srinivasan, K., Redi, M., Clinchant, S. ephane, & Lin, J. (2023). AToMiC: An Image/Text Retrieval Test Collection to Support Multimedia Content Creation ArXiv, abs/2304.01961. https://doi.org/10.48550/arXiv.2304.01961
Bauer, C., Carterette, B., Ferro, N., Fuhr, N., Beel, J., Breuer, T., … Zobel, J. (2023). Report on the Dagstuhl Seminar on Frontiers of Information Access Experimentation for Research and Education SIGIR Forum, 57, 1-7. https://doi.org/10.1145/3636341.3636351
Ren, H., Mousavi, A., Pacaci, A., Chowdhury, S. R., Mohoney, J., Ilyas, I., … Rekatsinas, T. (2023). Fact Ranking Over Large-Scale Knowledge Graphs With Reasoning Embedding Models IEEE Data Engineering Bulletin, 46, 126-139. Retrieved from http://sites.computer.org/debull/A23june/p126.pdf
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
Dadvar, V., Golab, L., & Srivastava, D. (2023). POEM: Pattern-Oriented Explanations of Convolutional Neural Networks Proceedings of the VLDB Endowment (PVLDB), 16, 3192-3200. https://doi.org/10.14778/3611479.3611518
Hebert, L., Golab, L., Poupart, P., & Cohen, R. (2023). FedFormer: Contextual Federation With Attention in Reinforcement Learning Presented at the FedFormer: Contextual Federation With Attention in Reinforcement Learning conference. https://doi.org/10.5555/3545946.3598716