Agent Swarm Cuts Complex Task Latency Up To 4.5×
Kimi K2.5 couples joint text-vision training with dynamically scheduled parallel subagents, improving agentic search scores while reducing time to target quality.
Aug 13, 20264 min2602.02276
Yichi Zhang
3 articles on SOTA Papers
Kimi K3 Brings Open Weights Closer to Frontier Agents
A 2.8T-parameter MoE combines Delta Attention, 16-of-896 expert routing, and agentic reinforcement learning to approach leading proprietary systems at lower task cost.
Aug 10, 20264 min2607.24653
Orca Unifies World Modeling Across Text, Vision, and Action
Next-State-Prediction trains a shared latent space from video, events, and VQA data, improving balanced downstream readouts with a frozen backbone.
Jul 28, 20265 min2606.30534