MultiLogBench shows that LLM performance on automated logging varies substantially across programming languages, demonstrating that single-language evidence is insufficient for general claims about model behavior or tool design.
Proceedings of the 33rd ACM International Conference on the Foundations of Software Engineering, June 23, 75–86
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Single-Language Evidence Is Insufficient for Automated Logging: A Multilingual Benchmark and Empirical Study with LLMs
MultiLogBench shows that LLM performance on automated logging varies substantially across programming languages, demonstrating that single-language evidence is insufficient for general claims about model behavior or tool design.
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AIReSim: A Discrete Event Simulator for Large-scale AI Cluster Reliability Modeling
AIReSim is a discrete event simulator for evaluating failure mitigation, recovery, and capacity planning decisions in large AI clusters.
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The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences
The paper reduces a broad set of prompt engineering techniques to six core approaches and applies them to life sciences use cases while addressing common LLM pitfalls.