What is recorded here?
Integrated balanced expert execution, memory-aware hybrid-model kernels and persistent rollout/sandbox states to train long-horizon agents with million-token trajectories in Kimi K3.
Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.
Scientific scope
System-level integration beyond K2, not invention of KDA, Attention Residuals, latent experts or on-policy distillation. Model size alone is not the contribution. Reported scaling/agent outcomes are not independently reproduced; release license is model-specific.
Read the original work
- Kimi K3: Open Frontier Intelligence
- Kimi Team: persistent long-horizon agent-training infrastructure — official supporting account
This English explanation is an editorial reading view. It does not replace the complete original work or certify its science.
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English catalogue narrative
Kimi Team: persistent long-horizon agent-training infrastructure
Integrated balanced expert execution, memory-aware hybrid-model kernels and persistent rollout/sandbox states to train long-horizon agents with million-token trajectories in Kimi K3.
Scientific scope
System-level integration beyond K2, not invention of KDA, Attention Residuals, latent experts or on-policy distillation. Model size alone is not the contribution. Reported scaling/agent outcomes are not independently reproduced; release license is model-specific.
Reading status
This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.
People and systems
Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.