Note

Medium Risk
Changes MoE expert selection on the training forward path when filtering is enabled, which can alter gradients and load balancing; default-off config limits blast radius.

Overview
Adds optional plausibility filtering for MoE router replay during RL training. With trainer.router_replay_score_threshold_ratio set above 0, each inference-replayed expert is kept only if the trainer router’s gate score for that expert is at least that fraction of the trainer’s weakest top-k score for the token; rejected slots are backfilled from the trainer’s own top-k picks. The default 0 leaves behavior unchanged (strict replay of inference routing).

Wiring: new trainer config field, configure_router_replay_filter applied at model init when router replay is on, and logic in TokenChoiceTopKRouter plus docs for the inference/trainer TOML knobs. torch.histc inputs are cast to float where needed.

^{Reviewed by Cursor Bugbot for commit 7e7f36f. Bugbot is set up for automated code reviews on this repo. Configure here.}