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

Density-Based Probabilistic Graphical Models for Adaptive Multi-Target Encirclement of AAV Swarm

Abstract: Multi-target encirclement with autonomous aerial vehicle (AAV) swarms is critical for military and civilian applications such as surveillance and disaster response. Existing methods face ...
GitHub

Any6D: Model-free 6D Pose Estimation of Novel Objects

We introduce Any6D, a model-free framework for 6D object pose estimation that requires only a single RGB-D anchor image to estimate both the 6D pose and size of unknown objects in novel scenes. Unlike ...