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Found 4 papers, 2 papers with code
A Careful Examination of Large Language Model Performance on Grade School Arithmetic
Large language models (LLMs) have achieved impressive success on many benchmarks for mathematical reasoning.
Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models
Calibration of deep learning models is crucial to their trustworthiness and safe usage, and as such, has been extensively studied in supervised classification models, with methods crafted to decrease miscalibration.
A workflow for segmenting soil and plant X-ray CT images with deep learning in Googles Colaboratory
Recent advances in machine learning, specifically the application of convolutional neural networks to image analysis, have enabled rapid and accurate segmentation of image data.
Simultaneously Predicting Multiple Plant Traits from Multiple Sensors via Deformable CNN Regression
Here, we introduce a relatively simple convolutional neural network (CNN) model that accepts multiple sensor inputs and predicts multiple continuous trait outputs - i. e. a multi-input, multi-output CNN (MIMO-CNN).
