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OpenAI now replays old conversations through new models before it ships them
OpenAI has built a pre-release testing system that feeds real, de-identified conversation starters from past users into ...
Kushal Agarwal is an expert analyst in energy and power sectors. He is currently a product manager at DSP Blackrock Mutual Fund. Pete Rathburn is a copy editor and fact-checker with expertise in ...
This post may contain links from our sponsors and affiliates, and Flywheel Publishing may receive compensation for actions taken through them. Predicting cryptocurrency prices is challenging because ...
For the low efficiency and poor generalization ability of path planning algorithm of industrial robots, this work proposes an adaptive field co-sampling algorithm (AFCS). Firstly, the environment ...
This repository contains the complete codebase for training and evaluating energy-based diffusion models for molecular dynamics simulations. Our approach enables a single model to perform both ...
Realistic maritime scene simulation remains a challenge in the field of visual simulation for maritime simulators and is widely applied in ocean engineering and computer graphics. High-fidelity ...
Language models often repeat themselves and fall back on stereotypical answers after training. Verbalized Sampling is a simple prompt technique designed to make AI responses less repetitive.
Birth–death-mutation-sampling (BDMS) models have a wide variety of applications in biology, including phylogenetics, epidemiology, and cancer genomics. Simulating evolutionary trees under these models ...
Abstract: Seismic wave forward simulation is the basis of seismic inversion and imaging. In recent years, deep learning methods represented by physics-informed neural networks (PINNs) have been widely ...
Abstract: We propose a sample-based model predictive control (MPC) method for collision-free navigation that uses a normalizing flow as a sampling distribution, conditioned on the start, goal, ...
With the development of quantum computing, the application of quantum neural networks will be more and more extensive, and its security will also face more challenges. Although quantum communication ...
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