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cs.LG2026
Scalable In-Context Reinforcement Learning with Recurrent Algorithm Distillation
Yuanqing Ma, Zhenrui Zheng, Chenjun Xiao
Algorithm Distillation (AD) has demonstrated the remarkable ability of Transformers to perform in-context reinforcement learning without explicit weight updates. However, capturing…
cs.CL2026
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…