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Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks.

, , , , , , and . NeurIPS, page 6695-6706. (2021)

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Truth or backpropaganda? An empirical investigation of deep learning theory., , , , and . ICLR, OpenReview.net, (2020)The Uncanny Similarity of Recurrence and Depth., , , , and . ICLR, OpenReview.net, (2022)Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks., , , , , , and . NeurIPS, page 6695-6706. (2021)Rethinking LLM Memorization through the Lens of Adversarial Compression., , , , and . CoRR, (2024)Transformers Can Do Arithmetic with the Right Embeddings., , , , , , , , , and 1 other author(s). CoRR, (2024)Universal Guidance for Diffusion Models., , , , , , and . ICLR, OpenReview.net, (2024)NEFTune: Noisy Embeddings Improve Instruction Finetuning., , , , , , , , , and 3 other author(s). ICLR, OpenReview.net, (2024)Adversarial Attacks on Machine Learning Systems for High-Frequency Trading., , , , , and . CoRR, (2020)End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking., , , , , , and . NeurIPS, (2022)Reckoning with the Disagreement Problem: Explanation Consensus as a Training Objective., , , , and . AIES, page 662-678. ACM, (2023)