Remark. Trajectory compression and feedback acquisition [ftip-006A]
Remark. Trajectory compression and feedback acquisition [ftip-006A]
The NExt construction Low-rank optimization trajectories modeling for LLM RLVR acceleration[chen2026lowrank] motivates a distinction between following a predictable parameter path and acquiring information from new rollouts. Low-rank dominance of saved differences does not imply linear future motion, invariance across parameterizations, or preservation of optimizer state.
A cost comparison includes checkpoint storage, decomposition, predictor training, extrapolation, and recovery updates. Bounding independent-evaluation regret additionally requires stability assumptions connecting parameter forecasts to the evaluated outcome.