Massive AI-generated numerical certificates resist Lean encoding
DimitrisPapail · x · 2026-09-15
Responding to whether such certificates can feasibly be encoded and checked in Lean, Papail argues the obstacle is that the proof is a ton of distinct inputs, bounds, and tables with poor compressibility. Example: an upper bound proof states that if chosen probability distributions and numerical tables satisfy every prescribed inequality, then capacity is at most some value.
More from Research
- Elo-per-token Analysis Explains Why LLM Agents Scale Fast Then Slow Down — Kaiyuan Liu · 2026-09-15
- KaiNinja Extends Native 3D Generators to Part-Level Outputs — AlayaLab · 2026-09-15
- Google: Structured Intermediate Specs Unlock Diverse UI Exploration for Vibe Design Agents — google · 2026-09-15
- Fruit fly brain fully mapped: 166k neurons, roughly a 1B-parameter SLM — anselm · 2026-09-15
- SmartNews Co-founder Ken Suzuki Launches ALife Institute in Kyoto with Nintendo Family Backing — Hidenori8Tanaka · 2026-09-15
- Open-source libgnss++ hits ~10mm static accuracy using Japan's CLAS corrections, no base station — rsasaki0109 · 2026-09-15