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cs.AI2026
Quantum Incremental Learning with Mixed State Prototypes
Yu Wu, Qianli Zhou, Xinyang Deng +3
Incremental learning models are required to learn new classes sequentially without catastrophic forgetting, while operating under parameter and memory constraints. In the Noisy Int…
cs.RO2026
FibVLA: An Efficient Temporal Vision-Language-Action Model with Fibonacci Sampling
Li Lin, Wujun Xu, Weiwei Meng +3
Vision-language-action models (VLAs), which leverage the cognition of multimodal information to infer physical-world actions, provide a generalized solution for embodied AI applica…
quant-ph2026
Stochastic Multipath Routing for High-Throughput Entanglement Distribution in Quantum Repeater Networks
Ankit Mishra, Kang Hao Cheong
Quantum repeater networks distribute entanglement over lossy links while many users share a limited pool of entangled pairs. Most existing routing schemes either always use a singl…