Calibrated accommodation pairs reward dialect matching in post-training
Across 10 open lineages, adjusted DPO still favored British and Australian spelling over AAE and Singlish.
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Stories tagged #preference-data
onPanda: Efficient Annotation of On-Policy Alignment Data for LLMs and Agents via Token-Level Correction
onPanda cuts median alignment annotation time 52% via token-level correction that keeps data on-policy for SFT and preference training.
onPanda: Efficient Annotation of On-Policy Alignment Data for LLMs and Agents via Token-Level Correction
onPanda corrects the first bad token and regenerates, cutting median alignment-annotation time by 52%.