New Paper: Self-Distillation May Not Suit Thinking Models
amaarora · x · 2026-07-17
A new paper takes a closer look at on-policy self-distillation (OPSD) for thinking models.
The authors point out that OPSD was originally seen as a promising path for recursive self-improvement, as thinking models can leverage their own "privileged information" for reasoning, verification, and error correction. However, the experimental results were surprising: OPSD might actually degrade the performance of thinking models.
More from Research
- Nature paper images cellular activity across all organs, revealing body-wide circuits — arjunrajlab · 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
- Apodex Launches TRACES, First Benchmark for Evaluating 'Discoverative AI' on Real-World Problems — Faheem_uh · 2026-09-11
- TRACES grades the process, not the answer: six-dimension eval for open-ended AI science — Faheem_uh · 2026-09-11
- Apodex launches TRACES, a benchmark grading AI on open-ended discovery instead of known answers — Faheem_uh · 2026-09-11