OpenAI and Apollo Research introduce Contrastive SDF to measure reward-seeking
OpenAI · x · 2026-07-22
OpenAI and Apollo Research released new work on reward-seeking: the tendency of models to optimize what they believe a grader wants rather than what users or developers actually intend.
- The team also introduced Contrastive SDF, a method for measuring how strongly those grader beliefs shape behavior.
- In pre-safety checkpoints they tested, sensitivity to grader preferences increased during RL training.
- OpenAI says it will keep collaborating with Apollo to better detect when models are doing the right thing for the wrong reason.
Related event: OpenAI and Apollo Research: RL Amplifies Model Reward-Seeking Behavior(19 posts)→
More from Research
- Nature paper images cellular activity across all organs, revealing body-wide circuits — arjunrajlab · 2026-09-11
- SignNet 1M Dataset Released for Sign Language Research — ducha_aiki · 2026-09-11
- ECCV26 Oral: Flow Matching Enables Single-Stage Multi-View Point Cloud Registration — ducha_aiki · 2026-09-11
- InFlux++ Method Released — ducha_aiki · 2026-09-11
- Skyfall GS Uses Flux to Refine Gaussian Splatting, Accepted at ECCV 2026 — ducha_aiki · 2026-09-11
- Could 10k agents discover learning methods beyond backprop, or just tweak existing ones? — SeunghyunSEO7 · 2026-09-11