14 citations · 16 across the 8 of their papers we have counts for
8 papers
PANDA: A Matrix-Free Differentiable NMPC Solver via Proximal Averaged Quasi-Newton with Adaptive Linesearch Algorithm
Yuankun Chen, Zifei Nie, Xun Gong +2
Differentiable nonlinear model predictive control (NMPC) provides a principled way to embed optimal control structure into end-to-end learning paradigms, but its practical use is o…
Kimi K3: Open Frontier Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +398
We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…
Kimi K2.5: Visual Agentic Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +333
We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…
A Gauss-Newton-Induced Structure-Exploiting Algorithm for Differentiable Optimal Control
Yuankun Chen, Zifei Nie, Xun Gong +2
Differentiable optimal control, particularly differentiable nonlinear model predictive control (NMPC), provides a powerful framework that enjoys the complementary benefits of machi…
Kimi K2: Open Agentic Intelligence
Kimi Team, Yifan Bai, Yiping Bao +195
We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which…
Modeling Earth-Scale Human-Like Societies with One Billion Agents
Haoxiang Guan, Jiyan He, Liyang Fan +10
Understanding the dynamic evolution of complex social phenomena requires both high-fidelity modeling of human behavior and large-scale simulations. Traditional agent-based models (…
Quantum Recurrent Neural Networks with Encoder-Decoder for Time-Dependent Partial Differential Equations
Yuan Chen, Abdul Khaliq, Khaled M. Furati
Nonlinear time-dependent partial differential equations are essential in modeling complex phenomena across diverse fields, yet they pose significant challenges due to their computa…
Self-Organizing State-Space Models with Artificial Dynamics
Yuan Chen, Mathieu Gerber, Christophe Andrieu +1
We consider the problem of performing parameter and state inference in a state-space model (SSM) parametrized by a static parameter . A popular idea to address this problem cons…