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Design Docs Are All You Need: An AI-native Machine-Learning Performance Tool

Paper recorded by Signals 4 on 2026-09-04 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.AI · 人工智能 · first seen 2026-09-07

Abstract

Machine-learning performance modeling is a uniquely hostile terrain for long-lived software: the assumptions baked into today's abstractions are invalidated by tomorrow's models and systems, forcing perpetual refactoring of performance-modeling frameworks. Meanwhile, AI coding agents have become fast and capable enough that regenerating an entire library is cheaper than paying down the tech debt o

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#171 most recent of 300 cs.AI papers we have recorded · ↑ newer: When LLM Decompilers Recompile More and Preserve Less · ↓ older: Who Should Grade My Work? Student Perspectives on Transparent AI-Assis

Cite this page: Design Docs Are All You Need: An AI-native Machine-Learning Performance Tool: the #171 most recent of 300 cs.AI papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/design-docs-are-all-you-need-an-ai-native-machine-learning-performance-tool.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json

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