GitHub

uqlm: Uncertainty Quantification for Language Models

UQLM provides a suite of response-level scorers for quantifying the uncertainty of Large Language Model (LLM) outputs. Each scorer returns a confidence score between 0 and 1, where higher scores ...
TechCrunch

Thinking Machines Lab wants to make AI models more consistent

There’s been great interest in what Mira Murati’s Thinking Machines Lab is building with its $2 billion in seed funding and the all-star team of former OpenAI researchers who have joined the lab. In a ...
IEEE

Probabilistic power flow considering variable bandwidth kernel density estimation for traction substation loads of high-speed railways

Abstract: A probabilistic power flow method considering variable bandwidth kernel density estimation (VKDE) for traction substation loads of high-speed railways is proposed. A variable bandwidth ...
IEEE

Jitter analysis based on kernel density estimation and dual-dirac

Abstract: Accurate jitter analysis is critical for next-generation I/O designs. In this paper, a method to separate deterministic jitter (DJ) and random jitter (RJ ...