[2607.11859] Can LLMs Perform Deep Technical Comprehension of Computer Architecture Papers?

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arXiv:2607.11859 (cs)

[Submitted on 13 Jul 2026]

Title:Can LLMs Perform Deep Technical Comprehension of Computer Architecture Papers?

Authors:Nishant Aggarwal, Ayushi Dubal, Sreeraj Kannakarankodi, Ian McDougall, Adarsh Mittal, Vishnu Ramadas, Noah Scott, Ranganath Selagamsetty, Weichu Yang, Karthikeyan Sankaralingam<br>View a PDF of the paper titled Can LLMs Perform Deep Technical Comprehension of Computer Architecture Papers?, by Nishant Aggarwal and 9 other authors

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Abstract:Can large language models perform deep technical comprehension of computer architecture papers -- not summarization, but structured critique that names the core mechanism, surfaces buried assumptions, and connects a contribution beyond its own scope? We study Gauntlet, an open-source pipeline that analyzes a paper through five independent expert-persona reviewers and an adversarial synthesis stage. On 20 ISCA 2025 and HPCA 2026 papers, ten researchers each wrote their own analyses and then judged, for papers other than their own, the human analysis against Gauntlet's. Across the 20 comparisons evaluators preferred Gauntlet in 15 (human in 4, one tie); its advantage is significant on per-analyst totals (paired Wilcoxon, p

Comments:<br>4 pages, 1 figure

Subjects:

Computers and Society (cs.CY); Hardware Architecture (cs.AR); Multiagent Systems (cs.MA)

Cite as:<br>arXiv:2607.11859 [cs.CY]

(or<br>arXiv:2607.11859v1 [cs.CY] for this version)

https://doi.org/10.48550/arXiv.2607.11859

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arXiv-issued DOI via DataCite (pending registration)

Submission history<br>From: Ranganath Selagamsetty [view email]<br>[v1]<br>Mon, 13 Jul 2026 17:45:58 UTC (1,070 KB)

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