Test-Time 'Breadth' in LLMs: Scaling Inference Without Pricey Tree Search
zhaoran_wang · x · 2026-07-04
Research institute tilderesearch initiated a technical thread exploring how to grant language models more expressive test-time "breadth" without relying on expensive full solution tree searches. By leveraging long Chain-of-Thought (long CoT), it achieves more efficient inference scaling. This is a methodological discussion focused on inference and test-time compute.
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