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cs.LG2025
CarBoN: Calibrated Best-of-N Sampling Improves Test-time Reasoning
Yung-Chen Tang, Pin-Yu Chen, Andrea Cavallaro
Allocating more computation during inference time (test-time scaling) improves language model performance, especially for reasoning tasks. However, popular methods like Best-of-…
cs.LG2024★ 2 cited
Defining and Evaluating Physical Safety for Large Language Models
Yung-Chen Tang, Pin-Yu Chen, Tsung-Yi Ho
Large Language Models (LLMs) are increasingly used to control robotic systems such as drones, but their risks of causing physical threats and harm in real-world applications remain…