Noise-Robust De-Duplication at Scale. - Emily Silcock; Luca D'Amico-Wong; Jinglin Yang; Melissa Dell (ICLR, 2023)

American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers. - Melissa Dell; Jacob Carlson; Tom Bryan; Emily Silcock; Abhishek Arora 003; Zejiang Shen 001; Luca D'Amico-Wong; Quan Le; Pablo Querubin; Leander Heldring (NeurIPS, 2023)

Understanding and Mitigating Extrapolation Failures in Physics-Informed Neural Networks. - Lukas Fesser; Richard Qiu; Luca D'Amico-Wong (CoRR, 2023)

Strategic Recommendation: Revenue Optimal Matching for Online Platforms (Student Abstract). - Luca D'Amico-Wong; Gary Qiurui Ma; David C. Parkes (AAAI, 2024)

Data Contamination Report from the 2024 CONDA Shared Task. - Oscar Sainz; Iker García-Ferrero; Alon Jacovi; Jon Ander Campos; Yanai Elazar; Eneko Agirre; Yoav Goldberg; Wei-Lin Chen; Jenny Chim; Leshem Choshen; Luca D'Amico-Wong; Melissa Dell; et al. (CONDA, 2024)

Newswire: A Large-Scale Structured Database of a Century of Historical News. - Emily Silcock; Abhishek Arora 003; Luca D'Amico-Wong; Melissa Dell (NeurIPS, 2024)

Disrupting Bipartite Trading Networks: Matching for Revenue Maximization. - Luca D'Amico-Wong; Yannai A. Gonczarowski; Gary Qiurui Ma; David C. Parkes (EC, 2024)

Easy as ABCs: Unifying Boltzmann Q-Learning and Counterfactual Regret Minimization. - Luca D'Amico-Wong; Hugh Zhang; Marc Lanctot; David C. Parkes (CoRR, 2024)