Computer Science, Machine Learning
Author: LLama 2 7B Chat
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LLaMA-2, the next generation of LLaMA. Meta trained and released LLaMA-2 in three model sizes: 7, 13, and 70 billion parameters. The model architecture remains largely unchanged from that of LLaMA-1 models, but 40% more data was used to train the foundational models. The accompanying preprint also mentions a model with 34B parameters that might be released in the future upon satisfying safety targets.
Computer Science, Computer Vision and Pattern Recognition
Event Recognition in Laparoscopic Gynecology Videos
Computer Science, Computer Vision and Pattern Recognition
Enhancing Deep Neural Networks with Weight Normalization
Bio-Inspired Flight and Landing Motions: A Comprehensive Analysis of Bird Behaviors
Computer Science, Computer Vision and Pattern Recognition
Training Models in Personal Devices via Interactive Masked Autoencoders
Computer Science, Machine Learning
Enhancing Generalization in Deep Neural Networks via Parameter Isolation
Computer Science, Data Structures and Algorithms
Online Graph Coloring: A Comprehensive Introduction
Computer Science, Human-Computer Interaction
Framing Esports’ JEDI Issues: A Case Study in Media Irresponsibility
Computer Science, Machine Learning
Aligning Neural Populations via Unsupervised Domain Adaptation
Optimizing MCMC Inference with Weighted Riesz Particles
Computer Science, Machine Learning
Optimizing Materials or Chemicals Efficiently in Experimental Settings with Bayesian Optimization
Computer Science, Machine Learning
Climate and Economics: A Comprehensive Analysis of Food Crises
Computer Science, Computer Vision and Pattern Recognition
Fine-tuning Mean Embedding Classifier for High-Fidelity Face Recognition
Electrical Engineering and Systems Science, Image and Video Processing
Adaptive Weighting Schemes for Heteroscedastic Noise in Medical Image Registration
Electrical Engineering and Systems Science, Image and Video Processing
Enhancing Echo Cardiography Segmentation via Self-Supervised Learning
Computer Science, Machine Learning
Maximum Model Accuracy for Neural Networks in Image Recognition
Computer Science, Machine Learning
Reducing Redundancy in Sub-Networks via Information Bottleneck
Computer Science, Computers and Society
Building Trust in Autonomous Ferries: A Formal Approach to Earn Human Confidence
Quantitative Biology, Quantitative Methods
ESM2 Feature Optimization for Supercomputing Center’s Performance in Nucleic Acid-Binding Residue Prediction
Computer Science, Machine Learning