Experimental reward models locate worst-scored Gemma SFT outputs
kalomaze · x · 2026-08-21
The author is building experimental reward models and searching for the lowest-scored samples within Gemma SFT outputs. This process successfully located some particularly poor generations at the tail end of the distribution.
More from Research
- 12 papers in 12 months: AI researchers debate flawed academic metrics — yoavgo · 2026-08-21
- Debating the semantic boundary between 'sealed sandbox' and 'frozen evaluation protocol' in agent evals — Kanu-animallover · 2026-08-21
- tldraw intern ships: clustering on-canvas comments without measuring a thing — max__drake · 2026-08-21
- Jie Tang on scaling history: FLOPs were intelligence, parameters were knowledge — cedric_chee · 2026-08-21
- Brainless Slime Mold Recreated Tokyo's Rail Network in 26 Hours — aigleeson · 2026-08-21
- Agent-Aware Architecture: Explicit Intent Layer for Token-Efficient Web Agents — sierracatalina · 2026-08-21