{"total":23,"rows":[{"id":"2406.06811","title":"Learning Continually by Spectral Regularization","created":"2024-06-10","cited_by_count":34,"area":null},{"id":"2410.20634","title":"Plastic Learning with Deep Fourier Features","created":"2024-10-27","cited_by_count":14,"area":null},{"id":"2506.03951","title":"Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective","created":"2025-06-04","cited_by_count":14,"area":null},{"id":"2410.20098","title":"Self-Normalized Resets for Plasticity in Continual Learning","created":"2024-10-26","cited_by_count":11,"area":null},{"id":"2507.20057","title":"What Can Grokking Teach Us About Learning Under Nonstationarity?","created":"2025-07-26","cited_by_count":8,"area":null},{"id":"2602.08040","title":"FIRE: Frobenius-Isometry Reinitialization for Balancing the Stability-Plasticity Tradeoff","created":"2026-02-08","cited_by_count":7,"area":null},{"id":"2502.01342","title":"Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss","created":"2025-02-03","cited_by_count":6,"area":null},{"id":"2508.00212","title":"Reinitializing weights vs units for maintaining plasticity in neural networks","created":"2025-07-31","cited_by_count":6,"area":null},{"id":"2509.22562","title":"Activation Function Design Sustains Plasticity in Continual Learning","created":"2025-09-26","cited_by_count":6,"area":null},{"id":"2509.23316","title":"C3-OWD: A Curriculum Cross-modal Contrastive Learning Framework for Open-World Detection","created":"2025-09-27","cited_by_count":5,"area":null},{"id":"2505.09486","title":"Preserving Plasticity in Continual Learning with Adaptive Linearity Injection","created":"2025-05-14","cited_by_count":2,"area":null},{"id":"2602.09234","title":"Do Neural Networks Lose Plasticity in a Gradually Changing World?","created":"2026-02-09","cited_by_count":2,"area":null},{"id":"2507.04683","title":"Recovering Plasticity of Neural Networks via Soft Weight Rescaling","created":"2025-07-07","cited_by_count":1,"area":null},{"id":"2604.13521","title":"C-voting: Confidence-Based Test-Time Voting without Explicit Energy Functions","created":"2026-04-15","cited_by_count":1,"area":null},{"id":"2605.04269","title":"Adapt or Forget: Provable Tradeoffs Between Adam and SGD in Nonstationary Optimization","created":"2026-05-05","cited_by_count":1,"area":null},{"id":"2606.24752","title":"Can Scale Save Us From Plasticity Loss in Large Language Models?","created":"2026-06-23","cited_by_count":1,"area":null},{"id":"2507.10637","title":"A Simple Baseline for Stable and Plastic Neural Networks","created":"2025-07-14","cited_by_count":0,"area":null},{"id":"2603.00253","title":"CoPeP: Benchmarking Continual Pretraining for Protein Language Models","created":"2026-02-27","cited_by_count":0,"area":null},{"id":"2606.24007","title":"Fast and Slow Variational Continual Learning","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2607.00377","title":"SAOT: Self-Supervised Continual Graph Learning with Structure-Aware Optimal Transport","created":"2026-07-01","cited_by_count":0,"area":null},{"id":"2608.04358","title":"NeuMoSync: End-to-End Neuromodulatory Control for Plasticity and Adaptability in Continual Learning","created":"2026-08-05","cited_by_count":0,"area":null},{"id":"2608.12874","title":"Sustaining Plasticity via Learnable Wavelet Activations in Continual Learning","created":"2026-08-13","cited_by_count":0,"area":null},{"id":"2610.16923","title":"Minimax Optimality of Shampoo for Nonstationary Stochastic Optimization","created":"2026-10-12","cited_by_count":0,"area":null}],"next_cursor":null}