An iSVD-based adaptive ROM framework updates reduced bases with occasional full-order snapshots, showing improved accuracy and efficiency over direct adaptation baselines on Burgers, Sod, and rotating detonation engine problems.
Shivam Garg, Dimitris Tsipras, Percy Liang, and Gregory Valiant
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Direction maps and pinwheel structures in MT emerge spontaneously when a spatiotemporal deep network is trained on videos with contrastive self-supervised learning and spatial regularization.
OjaKV introduces hybrid full-rank storage for key tokens combined with online low-rank KV cache compression via Oja's algorithm to support memory-efficient long-context LLM inference.
MPCS integrates eleven plasticity mechanisms and reaches a Normalized Efficiency Score of 94.2 on a 31-task benchmark, with ablations showing that removing EWC and Hebbian updates yields higher performance at lower cost.
citing papers explorer
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History-aware adaptive reduced-order models via incremental singular value decomposition
An iSVD-based adaptive ROM framework updates reduced bases with occasional full-order snapshots, showing improved accuracy and efficiency over direct adaptation baselines on Burgers, Sod, and rotating detonation engine problems.
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Self-organized MT Direction Maps Emerge from Spatiotemporal Contrastive Optimization
Direction maps and pinwheel structures in MT emerge spontaneously when a spatiotemporal deep network is trained on videos with contrastive self-supervised learning and spatial regularization.
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OjaKV: Context-Aware Online Low-Rank KV Cache Compression
OjaKV introduces hybrid full-rank storage for key tokens combined with online low-rank KV cache compression via Oja's algorithm to support memory-efficient long-context LLM inference.
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MPCS: Neuroplastic Continual Learning via Multi-Component Plasticity and Topology-Aware EWC
MPCS integrates eleven plasticity mechanisms and reaches a Normalized Efficiency Score of 94.2 on a 31-task benchmark, with ablations showing that removing EWC and Hebbian updates yields higher performance at lower cost.
- Attention-based PCA