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$Φ$-Bench: Can Large Language Models Engineer the Infrastructure That Powers Them?

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

Published 2026-09-09 on arXiv · recorded by Signals 4 on 2026-09-10

Category: cs.CL · 自然语言处理 · first seen 2026-09-10

Abstract

Large language models (LLMs) have demonstrated remarkable capabilities in reasoning and code generation, raising the prospect that they could assist in developing and optimizing the very infrastructure that powers them. However, existing benchmarks mainly focus on isolated kernels, predefined operators, or pre-specified optimization targets, and therefore fail to evaluate the ability of LLMs to pe

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#90 most recent of 186 cs.CL papers we have recorded · ↑ newer: The Answer Path and the Grounding Instruction in LLM Question Answerin · ↓ older: ReCite: Agentic Reasoning for Faithful Citation
Cite this page: $Φ$-Bench: Can Large Language Models Engineer the Infrastructure That Powers Them?: the #90 most recent of 186 cs.CL papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/bench-can-large-language-models-engineer-the-infrastructure-that-powers-them.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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