calibrated reasoning 1deferral mechanisms 1edge computing 1large language models 1uncertainty estimation 1
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stat.ML2026
Think Short, Defer Smart, Act, and Repeat: Calibrated Reasoning and Uncertainty-Aware Deferral for Edge LLM Agents
Amirmohammad Farzaneh, Osvaldo Simeone
The paper introduces Think Short, Defer Smart (TSDS), a framework for edge-deployed LLM agents that stops on-device reasoning when actions stabilize and defers uncertain actions to…
stat.ML2026
Statistically Valid Hyperparameter Selection: From Tuning to Guarantees
Amirmohammad Farzaneh, Osvaldo Simeone
Hyperparameter selection is a critical step in the deployment of modern artificial intelligence systems, given the need to tune degrees of freedom such as inference-time parameters…
stat.ML2026
Post-Selection Distributional Model Evaluation
Amirmohammad Farzaneh, Osvaldo Simeone
Formal model evaluation methods typically certify that a model satisfies a prescribed target key performance indicator (KPI) level. However, in many applications, the relevant targ…