Computer Science, Computer Vision and Pattern Recognition
Author: LLama 2 7B Chat
Page 109/179
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, Social and Information Networks
Content Moderation Strategies: A Review of the Literature
Computer Science, Cryptography and Security
DeepSight: A Practical Approach to Outlier Detection in Non-iid Data
Computer Science, Computer Vision and Pattern Recognition
Personalized Video Synthesis with Diffusion Models
Enhancing Sketch Recognition with Visual Clues
Computation and Language, Computer Science
Revolutionizing Aspect-Based Summarization with Open-Aspect Models
Secure Quantum Computation for Summation and Multiplication
Computer Science, Human-Computer Interaction
Indie Developers and AAA Games: The Shift in Gaming Industry Trends
Computer Science, Computer Vision and Pattern Recognition
Improving Deepfake Detection with Attention-based Localization and Global Feature Fusion
Computer Science, Computer Vision and Pattern Recognition
Neural Networks for 3D Model Reconstruction: A Survey
Computer Science, Computer Vision and Pattern Recognition
Generating Conditional 3D Implicit Functions via Shap-e
Computer Science, Computer Vision and Pattern Recognition
Enhancing Zero-Shot Segmentation with Domain Knowledge
Reducing Computational Effort in Process Systems Engineering through Artificial Neural Networks
Atmospheric and Oceanic Physics, Physics
ERA5 Global Reanalysis: A Collaborative Effort to Advance Climate Science
Computer Science, Machine Learning
Related Work in Machine Learning and Causal Inference: A Comprehensive Review
Computer Science, Machine Learning
Text-Driven Human Video Generation: A Survey of Recent Approaches
Computer Science, Information Theory
Directions for Future Research in Machine Learning
Computer Science, Computer Vision and Pattern Recognition
Improving Image Generation with Better Captions
Computer Science, Machine Learning
Efficient Extraction of Higher-Order Information in Neural Networks
Computer Science, Machine Learning