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RLHF & Preference Data
Alignment-grade preference signal from real domain experts.
Preference rankings, DPO pair generation, and reward-model training data, captured with rationales by your trusted evaluators.
Pairwise preference, with rationale
Every preference judgement comes with the why, short rationale text, optional rubric tags, and confidence. The signal you need for high-quality reward modeling.
- → Randomized A/B presentation with blinding
- → Tie-handling and ordinal-ranking for >2 candidates
- → Per-rubric tag scoring (helpfulness, safety, factuality)
- → Free-text rationale with hotkey templates
Prompt
"Explain why a yield curve inversion has historically preceded recessions."
Response A · +0.82
Walks through term-premium & expectation-hypothesis with examples.
Response B · −0.34
Surface-level claim, conflates correlation with causation.
Rationale
"A grounds claim in macro mechanics; B is loose and assumes the conclusion."
Built for the alignment workflow
DPO pair export
Approved batches export to JSONL with chosen/rejected pairs and rationales, drop straight into your trainer.
Reward-model formats
Output as Bradley-Terry pairs, K-wise rankings, or per-rubric scalar scores. We adapt to your training stack.
Calibration loops
Worqgrid resurfaces disagreements as calibration tasks so your rubric and your evaluators stay aligned.