48 citations · 50 across the 5 of their papers we have counts for
6 papers
MJev-Spatial: System One Spatial Intelligence via Native Attention Matching
Luozheng Qin, Yuhan Zhu, Changhai Zhou +9
Spatial intelligence lets an agent perceive and act in the physical world, and many of its judgments must be made at interaction rates: which spatial relation holds, how far an obj…
Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA
Mind Lab, :, Vin Bo +80
Macaron-V1 is an open agent-model family for experiential intelligence: learning from experience in real environments and continuing to learn after deployment. It is organized arou…
LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget
Changhai Zhou, Kieran Liu, Yuhua Zhou +17
Long-context RL post-training is constrained by the lifetime of state and gradients, not attention cost alone. In GRPO, one multi-million-token prompt must serve old-policy and ref…
Macaron-A2UI: A Model for Generative UI in Personal Agents
Fancy Kong, Congjie Zheng, Murphy Zhuang +8
As personal agents evolve to handle complex, user-centric tasks, static plain-text chat is rapidly becoming a bottleneck. Generative UI emerges as the necessary new interface layer…
Gaussian Process Kolmogorov-Arnold Networks
Andrew Siyuan Chen
In this paper, we introduce a probabilistic extension to Kolmogorov Arnold Networks (KANs) by incorporating Gaussian Process (GP) as non-linear neurons, which we refer to as GP-KAN…
Scaling Up Models and Data with and
Adam Roberts, Hyung Won Chung, Anselm Levskaya +40
Recent neural network-based language models have benefited greatly from scaling up the size of training datasets and the number of parameters in the models themselves. Scaling can…