Interactive transformer diagrams now include backpropagation, aiming at model self-understanding
vtabbott_ · x · 2026-10-22
Researcher vtabbott describes their interactive diagram project: backpropagation (training steps) is now integrated into diagrams like scaled dot-product attention, covering architectures from the original transformer to DeepSeek-V3, Kimi K3 and GLM-5.3, with views for pass/training, caching and quantization formats. The stated aim: develop 'the mathematical tools models will use to understand themselves'.
Related event: Interactive Transformer Diagram Adds Backpropagation Visualization(2 posts)→
More from Research
- Break-Glass paper lays out emergency biosecurity licensing regime for an AI biological incident — davidmanheim · 2026-10-22
- Lafa scales flow language models to 8B, matching AR quality at 2.5x throughput — AdtRaghunathan · 2026-10-22
- New paper: SMC sampling with integrator snippets yields principled HMC tuning strategies — michaelchchoi · 2026-10-22
- HKU-led team launches Embodied Playground, 410-task benchmark for model physical intelligence — YiMaTweets · 2026-10-22
- Chatlet: Generative UI That Emerges From Group Conversations — round · 2026-10-22
- NJU's Socratic Skill Learning hits 0.801 utility, beating distillation baselines — NJU-LINK · 2026-10-22