Unverified50% confidenceOpinionExact time
The authors of VASPO believe that simply combining self-distillation signals with GRPO (using GRPO to determine the update direction and using teacher signals for scaling) does not realize the true potential of the two signals.
1
Sources
50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedAt the scale of small models with a few hundred million parameters, reinforcement learning methods such as GRPO may not be applicable, as the models may be unable to produce positive samples of sufficient quality to provide an effective learning signal.68% similarUnverifiedAll three models failed to pass the GRPO stage; while GRPO showed slight improvement in teaching the models arithmetic, general capabilities degraded significantly.61% similarUnverifiedIn low-dimensional fine-tuning experiments on a math benchmark suite, LlMBO's fine-tuning gains matched or even exceeded those of GRPO, while using only a small fraction of the latter's compute and memory.57% similarUnverifiedSimply increasing model scale or extending training duration does not automatically solve the problem of hard tasks being neglected, because the root cause lies in the absence of the signal itself.52% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1032850API
curl https://kongchang.com/api/v1/knowledge/claims/1032850MCP
get_claim(id=1032850)