New claim: model architecture can improve scaling exponents
madhavsinghal_ · x · 2026-09-18
Akshay Vegesna shares a research claim that model architecture itself can improve scaling exponents — meaning architectural choices could structurally change how performance scales with compute and data, not just shift constants. Details are thin in the post, pending the full work.
More from Research
- Data Lab Argues Truly General Synthetic Data Matters More Than Architecture — Paimaamu · 2026-09-18
- 3DV 2027 opens Nectar Track call for papers, deadline Feb 15, 2027 — ftm_guney · 2026-09-18
- New Tool Lets You Search and Skim Anthropic's Released Mythos Transcript by Flagged Behaviors — round · 2026-09-18
- Experiment calibrates 48 attention heads down to 12, swapping the rest for band-diagonal sparse attention — ostrisai · 2026-09-18
- NVIDIA open-sources NeMo Data Designer: declarative synthetic data pipeline lifts Nemotron Nano v3 from 80.2% to 86.9% — dair_ai · 2026-09-18
- Hybrid Mamba-Transformer skips RoPE: Nemotron-style arch fixes Mamba's ICL and long-context weaknesses with few attention layers — gordic_aleksa · 2026-09-18