Unverified50% confidenceFactExact time
GRPO's supervision granularity is sequence-level, with the entire response sharing a single advantage value, so it cannot indicate which step in the reasoning chain went wrong.
1
Sources
50%
Confidence
Long-term
Relevance
10/20/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedAnswer-level advantage assignment algorithms like GRPO are not omnipotent; when the quality of sentences within an answer varies greatly, evenly distributing the advantage value dilutes the signal and may even reinforce wrong behavior.76% similarUnverifiedGRPO generates a group of candidate outputs for the same input and updates the model using intra-group relative reward signals rather than absolute reward signals, reducing reliance on an independent value network (critic).71% similarUnverifiedgrep can only return matching lines of text and cannot determine which results are truly valuable for the current task.69% similarUnverifiedThe core innovation of GRPO is the complete removal of the value network; it samples multiple responses to the same question to form a group, and uses the mean return within the group as the baseline.69% similarUnverifiedStandard GRPO samples multiple trajectories from the task's initial state, whereas ReTerm-GRPO changes the sampling starting point to states in which the agent itself has already failed.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1073347API
curl https://kongchang.com/api/v1/knowledge/claims/1073347MCP
get_claim(id=1073347)