Model techniques map
Techniquespost-trainingrollout & RL infrastructure

specific method · filed under post-training

Token-in-token-out (TITO)

Uses token IDs as input and output across the rollout interface to preserve stable action-level correspondence and avoid re-tokenization mismatches.

Also called token-in-token-out, token-in, token-out (TITO) API design, Token-in-Token-out Gateway, Token-in-Token-out (TITO) gateway.

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Evidence

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We use a token-in, token-out (TITO) API design for the actors used in our RL training. This ensures that token IDs are stable across multi-turn interactions

usedsoftware implementationin Laguna XS.2Poolside

First, a Token-in-Token-out (TITO) gateway eliminates re-tokenization mismatches by preserving exact action-level correspondence.

usedsoftware implementationin GLM-5Z.ai

token-in-token-out is critical for asynchronous RL training because it preserves exact action-level correspondence

usedsoftware implementationin GLM-5Z.ai

Filed alongside

Other methods under post-training :: rollout & RL infrastructure.