Computer Science, Cryptography and Security
Author: LLama 2 7B Chat
Page 138/179
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, Machine Learning
Combating Bias in AI-Driven Drug Discovery: A Novel Approach to Remove Irrelevant Attributes
Computer Science, Computer Vision and Pattern Recognition
Training Latent Diffusion Models for Image Generation
Computer Science, Computer Vision and Pattern Recognition
Comparative Study of 6D Object Pose Estimation Methods for Texture-Less Objects
Learning Rapidly, Yet Implicitly: Balancing Human Involvement in Robot Autonomy
Computation and Language, Computer Science
Exploring Limits of Transfer Learning with Unified Text-to-Text Transformer
Computer Science, Computer Vision and Pattern Recognition
Enhancing Distillation with Unsupervised Tasks: A New Frontier in Vision Transformers
Automatic Relational Data Augmentation for Machine Learning
Autonomous Racing: Developing High-Performance Software and Hardware for Unprecedented Levels of Independence
Electrical Engineering and Systems Science, Systems and Control
Understanding Segmental Phases of Matrices
Mathematics, Numerical Analysis
Nonlinear Dynamics and Approximation: A Comparative Study of Reduction Techniques
Computer Science, Networking and Internet Architecture
5G Brilliance: Unveiling T-Mobile’s Spectrum Strategy
Computation and Language, Computer Science
Understanding the Impact of Compression Techniques on Language Models’ Performance
Computer Science, Neural and Evolutionary Computing
Broadening the Scope of VNS Studies: A Review of Avenues and Challenges
Lightweight Communication and Marshaling in Robotics: A Survey
Computer Science, Machine Learning
Transformers vs RNNs in Spatiotemporal Data Imputation: A Comparative Study
Computer Science, Information Theory
Signal Analysis with Permutation Entropy: A Review
Computer Science, Machine Learning
Spectral Temporal Contrastive Learning: A Theoretical Analysis
Dynamical Systems, Mathematics