Limits of structures and the example of tree semi-lattices. - Pierre Charbit; Lucas Hosseini; Patrice Ossona de Mendez (Discret. Math., 2017)

Limits of mappings. - Lucas Hosseini; Jaroslav Nesetril; Patrice Ossona de Mendez (Eur. J. Comb., 2017)

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned. - Sewon Min; Jordan L. Boyd-Graber; Chris Alberti; Danqi Chen 001; Eunsol Choi; Michael Collins 001; Kelvin Guu; Hannaneh Hajishirzi; Kenton Lee; Jennimaria Palomaki; Colin Raffel; Adam Roberts; et al. (NeurIPS (Competition and Demos), 2020)

A Memory Efficient Baseline for Open Domain Question Answering. - Gautier Izacard; Fabio Petroni; Lucas Hosseini; Nicola De Cao; Sebastian Riedel 001; Edouard Grave (CoRR, 2020)

Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search. - Harsha Vardhan Simhadri; George Williams; Martin Aumüller 001; Matthijs Douze; Artem Babenko; Dmitry Baranchuk; Qi Chen 009; Lucas Hosseini; Ravishankar Krishnaswamy; Gopal Srinivasa; Suhas Jayaram Subramanya; Jingdong Wang 001 (NeurIPS (Competition and Demos), 2021)

Towards Unsupervised Dense Information Retrieval with Contrastive Learning. - Gautier Izacard; Mathilde Caron; Lucas Hosseini; Sebastian Riedel 001; Piotr Bojanowski; Armand Joulin; Edouard Grave (CoRR, 2021)

Improving Wikipedia Verifiability with AI. - Fabio Petroni; Samuel Broscheit; Aleksandra Piktus; Patrick Lewis 001; Gautier Izacard; Lucas Hosseini; Jane Dwivedi-Yu; Maria Lomeli; Timo Schick; Pierre-Emmanuel Mazaré; Armand Joulin; Edouard Grave; et al. (CoRR, 2022)

Few-shot Learning with Retrieval Augmented Language Models. - Gautier Izacard; Patrick Lewis 001; Maria Lomeli; Lucas Hosseini; Fabio Petroni; Timo Schick; Jane Dwivedi-Yu; Armand Joulin; Sebastian Riedel 001; Edouard Grave (CoRR, 2022)

Unsupervised Dense Information Retrieval with Contrastive Learning. - Gautier Izacard; Mathilde Caron; Lucas Hosseini; Sebastian Riedel 001; Piotr Bojanowski; Armand Joulin; Edouard Grave (Trans. Mach. Learn. Res., 2022)

PyTorch RPC: Distributed Deep Learning Built on Tensor-Optimized Remote Procedure Calls. - Shen Li; Pritam Damania; Luca Wehrstedt; Rohan Varma; Omkar Salpekar; Pavel Belevich; Howard Huang; Yanli Zhao; Lucas Hosseini; Wanchao Liang; Hongyi Jia; Shihao Xu; et al. (MLSys, 2023)

Atlas: Few-shot Learning with Retrieval Augmented Language Models. - Gautier Izacard; Patrick Lewis 001; Maria Lomeli; Lucas Hosseini; Fabio Petroni; Timo Schick; Jane Dwivedi-Yu; Armand Joulin; Sebastian Riedel 001; Edouard Grave (J. Mach. Learn. Res., 2023)

Improving Wikipedia verifiability with AI. - Fabio Petroni; Samuel Broscheit; Aleksandra Piktus; Patrick Lewis 001; Gautier Izacard; Lucas Hosseini; Jane Dwivedi-Yu; Maria Lomeli; Timo Schick; Michele Bevilacqua; Pierre-Emmanuel Mazaré; Armand Joulin; et al. (Nat. Mac. Intell., 2023)

The Faiss library. - Matthijs Douze; Alexandr Guzhva; Chengqi Deng; Jeff Johnson 004; Gergely Szilvasy; Pierre-Emmanuel Mazaré; Maria Lomeli; Lucas Hosseini; Hervé Jégou (CoRR, 2024)