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cs.CL2024★ 1 cited
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
Yinlam Chow, Guy Tennenholtz, Izzeddin Gur +7
Recent studies have indicated that effectively utilizing inference-time compute is crucial for attaining better performance from large language models (LLMs). In this work, we prop…
cs.CL2024
Finetuning Language Models to Emit Linguistic Expressions of Uncertainty
Arslan Chaudhry, Sridhar Thiagarajan, Dilan Gorur
Large language models (LLMs) are increasingly employed in information-seeking and decision-making tasks. Despite their broad utility, LLMs tend to generate information that conflic…