Model techniques map
Techniquespost-trainingreward modelling

general family · filed under post-training

Groupwise Agentic Grading

Uses an agentic grader to compare rollouts within a group and provide reward signals beyond binary test outcomes.

sources
3
models
2
lab adopt it
1
strongest
core

How sources treat it

One count per evidence span, weakest treatment to strongest.

used 2core 2

Documented in

Evidence

4 spans quoted from the sources, strongest treatment first.

we introduce groupwise agentic grading to provide more informative reward signals beyond binary test cases

coreevaluation onlyin MiMo-V2.6 RL trainingXiaomi

An agentic grader compares rollouts within each group

coretraining objectivein MiMo-V2.6-Flash-RLXiaomi

An agentic grader compares rollouts within each group

usedtraining objectivein MiMo-V2.6-Pro-RLXiaomi

the compute devoted to groupwise agentic grading.

usedtraining objectivein MiMo-V2.6

Filed alongside

Other methods under post-training :: reward modelling.