U.S. labs lean on RL while Chinese labs favor SFT on successful traces
goyalshaliniuk · x · 2026-07-22
A short observation on training trends across labs:
- U.S. AI labs appear to rely on RL more often.
- Chinese labs appear to use SFT on successful traces more often, and the author says this can be very competitive.
- Kimi K3 is cited as soft evidence for that claim.
The post is not a formal result, but a concise industry-level hypothesis about how reasoning models may be trained.
Related event: Divergent Sino-US Training Paradigms and New SFT Alignment Ideas(5 posts)→
More from Research
- Causal-only attention for non-generative tasks is wasteful, argues HF engineer — antoine_chaffin · 2026-09-11
- Catholic University of Chile researcher: scaling AI feedback is key to sustainable medical education — julianvarascom · 2026-09-11
- 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