onPanda: Token-Level Correction Cuts LLM Alignment Annotation Time by 52%
_akhaliq · x · 2026-09-23
onPanda is an open-sourced interactive tool for efficient annotation of on-policy alignment data for LLMs and agents, plus model inspection. Highlights:
Data annotation
- Reduces median annotation time by 52%
- Collects both SFT and preference data in the same workflow
- Produces SFT data with high on-policy fidelity (∆PPL < 1%)
- Captures token-level supervision with exact correction locations and naturally paired positive/negative examples
- Supports annotating agent trajectories with image, audio and video inputs
Model inspection and debugging
- Inspect each token's probability and top-k alternatives, steer LLM decoding at the token level
- Try SVG generation, web dev and agent tasks in the browser with no setup
Try it online (works on mobile); paper is available.
Related event: StepFun Open-Sources onPanda for Faster Alignment Data Labeling(3 posts)→
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