We train Context-1 fully on-policy using CISPO, a variant of GRPO. At each training step, 128 queries are drawn from a shuffled, interleaved mixture from training splits of our legal, patent, and web generated queries only. For each query, 8 independent environment instances are created for rollout, yielding 1,024 agent trajectories per step.
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2. Embrace the Global Shared Memory ModelTLA+ gives you a deliberate fiction: a global shared memory that all processes can read and write. This fiction is the foundation of its computational model, and understanding it is essential to thinking in TLA+.