most citedLife-Cycle Emissions of AI Hardware: A Cradle-To-Grave Approach and Generational Trends

8 citations · 15 across the 16 of their papers we have counts for

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cs.AI2026

ScientistTwo: Pioneering the Human Knowledge Frontier with Autonomous AI

Jaehyun Nam, Jinsung Yoon, Yanzhou Pan +4

Scientific discovery is defined by the ability to identify the boundaries of existing knowledge and venture into unexplored territory. The ultimate vision for AI in science is prob…

cs.AI2026

ArchAgent v2: A Case Study with the Data Prefetching Championship

Abraham Gonzalez, Raghav Gupta, Akanksha Jain +12

Agentic artificial intelligence has shown great promise in automating algorithm design, but scaling similar techniques to computer microarchitecture discovery remains challenging d…

cs.AI2026

ScientistOne: Towards Human-Level Autonomous Research via Chain-of-Evidence

Rui Meng, Bhavana Dalvi Mishra, Jiefeng Chen +10

Autonomous research agents produce competitive solutions and professional-looking manuscripts, yet their outputs contain verifiability failures undetectable by surface-level evalua…

cs.AI2026

ArchAgent: Agentic AI-driven Computer Architecture Discovery

Raghav Gupta, Akanksha Jain, Abraham Gonzalez +10

Agile hardware design flows are a critically needed force multiplier to meet the exploding demand for compute. Recently, agentic generative AI systems have demonstrated significant…

cs.AI2025★ 7 cited

Measuring the environmental impact of delivering AI at Google Scale

Cooper Elsworth, Keguo Huang, David Patterson +9

The transformative power of AI is undeniable - but as user adoption accelerates, so does the need to understand and mitigate the environmental impact of AI serving. However, no stu…