Test-Time Training vs Looped Models
DanielKhashabi · x · 2026-07-14
This is a blog post exploring the intersection of test-time training and looped models, written by the author during some downtime at ICML.
Titled "Loop deeper, or adapt?", the core focus is on whether models utilizing a looped/multi-turn reasoning structure should simply "loop deeper" during inference, or if they should perform adaptive updates at test time.
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