vespo-variational-sequence-rl

Stabilize off-policy RL training for LLMs by deriving principled importance weight reshaping from variational optimization. Instead of heuristic clamping, VESPO uses closed-form exponential weighting W^c1 * exp(c2*(1-W)) to suppress overweighted samples while maintaining smooth gradients. Enables stable training at 64× policy staleness and under fully async…

Independent GitHub snapshot · Automated classification · Original documentation governs