memorization capacity

Memorization and Expressivity in Transformers: A Learning-Theoretic Perspective AAAI 2026 On the scaling relationship between cloze probabilities and language model next-token prediction CoNLL 2026 Capacity Matters: a Proof-of-Concept for Transformer Memorization on Real-World Data ACL 2025 Memorization in Attention-only Transformers AISTATS 2025 On the Optimal Memorization Capacity of Transformers ICLR 2025 Memorization Capacity for Additive Fine-Tuning with Small ReLU Networks UAI 2024 Memorization Capacity of Multi-Head Attention in Transformers ICLR 2024 Memorization With Neural Nets: Going Beyond the Worst Case JMLR 2024 Memorization Capacity of Neural Networks with Conditional Computation ICLR 2023 Provable Memorization Capacity of Transformers ICLR 2023 Memorization and Optimization in Deep Neural Networks with Minimum Over-parameterization NeurIPS 2022 An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks NeurIPS 2021 Excess Capacity and Backdoor Poisoning NeurIPS 2021 Provable Memorization via Deep Neural Networks using Sub-linear Parameters COLT 2021 Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity NeurIPS 2019