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Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes., , , , , and . NeurIPS, (2020)Improving Self-Supervised Learning by Characterizing Idealized Representations., , , and . NeurIPS, (2022)Location Attention for Extrapolation to Longer Sequences., , , and . ACL, page 403-413. Association for Computational Linguistics, (2020)Learning to (Learn at Test Time): RNNs with Expressive Hidden States., , , , , , , , , and 2 other author(s). CoRR, (2024)Evaluating Self-Supervised Learning via Risk Decomposition., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 8779-8820. PMLR, (2023)Identifying the Risks of LM Agents with an LM-Emulated Sandbox., , , , , , , , and . ICLR, OpenReview.net, (2024)Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators., , , and . CoRR, (2024)Lossy Compression for Lossless Prediction., , , and . NeurIPS, page 14014-14028. (2021)Convolutional Conditional Neural Processes., , , , , and . ICLR, OpenReview.net, (2020)Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning., , , , and . CoRR, (2022)