4 citations · 6 across the 6 of their papers we have counts for
7 papers
Beyond Leaderboards: Tokenomics of Agentic Small Language Model Ensembles
Alexei N. Skurikhin, Emily M. Taylor, Nathan A. DeBardeleben
As large language models (LLMs) move from standalone assistants into agentic workflows, evaluation must extend beyond scalar leaderboard accuracy to account for operational reliabi…
From Benchmark Performance to Tool Deployment: Human-in-the-Loop Anomaly Detection
Mike Szklarzewski, CJ George, Gavin Smithson +10
Automated anomaly detection methods often report strong performance on curated academic benchmarks, but their behavior under real-world industrial conditions is less clear. In this…
Resiliency in Numerical Algorithm Design for Extreme Scale Simulations
Emmanuel Agullo, Mirco Altenbernd, Hartwig Anzt +33
This work is based on the seminar titled ``Resiliency in Numerical Algorithm Design for Extreme Scale Simulations'' held March 1-6, 2020 at Schloss Dagstuhl, that was attended by a…
TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications
Zitao Chen, Niranjhana Narayanan, Bo Fang +3
As machine learning (ML) has seen increasing adoption in safety-critical domains (e.g., autonomous vehicles), the reliability of ML systems has also grown in importance. While prio…
Failure Analysis and Quantification for Contemporary and Future Supercomputers
Li Tan, Nathan DeBardeleben
Large-scale computing systems today are assembled by numerous computing units for massive computational capability needed to solve problems at scale, which enables failures common…
Soft Error Resilience and Failure Recovery for Continuum Dynamics Applications
Li Tan, Marc Charest, Nathan DeBardeleben +2
The persistently growing resilience concerns of large-scale computing systems today require not only generic fault tolerance approaches, but also application-level resilience, due…