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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.DC2026

Energy Calculus: A Compositional Algebra of Energy in Computational Systems

Mosharaf Chowdhury, Jae-Won Chung, Jeff J. Ma +2

The paper introduces Energy Calculus, a compositional algebra that treats energy as a first‑class primitive, allowing systematic combination of energy measurements across sequentia…

cs.LG2026

TetriServe: Efficiently Serving Mixed DiT Workloads

Runyu Lu, Shiqi He, Wenxuan Tan +5

Diffusion Transformer (DiT) models excel at generating high-quality images through iterative denoising steps, but serving them under strict Service Level Objectives (SLOs) is chall…

cs.LG2026

Cornserve: A Distributed Serving System for Any-to-Any Multimodal Models

Jae-Won Chung, Jeff J. Ma, Jisang Ahn +4

Any-to-Any models are an emerging class of multimodal models that accept combinations of multimodal data (e.g., text, image, video, audio) as input and generate them as output. Ser…

cs.LG2026

Cornfigurator: Automated Planning for Any-to-Any Multimodal Model Serving

Jeff J. Ma, Jae-Won Chung, Jisang Ahn +5

Any-to-Any models are an emerging class of multimodal models that accept combinations of text and multimodal data as input and generate them as output, introducing heterogeneous co…

cs.LG2026

Where Do the Joules Go? Diagnosing Inference Energy Consumption

Jae-Won Chung, Ruofan Wu, Jeff J. Ma +1

Energy is now a critical ML computing resource. While measuring energy consumption and observing trends is a valuable first step, accurately understanding and diagnosing why those…

cs.LG2025

The ML.ENERGY Benchmark: Toward Automated Inference Energy Measurement and Optimization

Jae-Won Chung, Jeff J. Ma, Ruofan Wu +5

As the adoption of Generative AI in real-world services grow explosively, energy has emerged as a critical bottleneck resource. However, energy remains a metric that is often overl…