Computation and Language, Computer Science
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, Cryptography and Security
Enhancing KEM-IND-CCA Security Through Forward Path Truncation and Tagging Attack Handling
Computer Science, Machine Learning
Diffusion Models for Unsupervised Representation Learning: A Comparative Study
Incremental Learning of Motor Skills Through Demonstrations
Computer Science, Machine Learning
Assessing Generalization of Neural Networks: A Comprehensive Review
Electrical Engineering and Systems Science, Image and Video Processing
Deepfake Detection: A Focused Approach for Identities
Computation and Language, Computer Science
Unlocking the Potential of Large Language Models: A Survey of Recent Advances and Challenges in Natural Language Processing
Managing Inconsistent Databases: A Guide to Efficient Query Answering
Computer Science, Computers and Society
Safeguarding Safe AI Development
Computer Science, Information Retrieval
Simulating User Behavior in Conversational AI: A Comprehensive Review
Computer Science, Social and Information Networks
Improved Approximate Symmetry Coefficients for Better Permutation Generation
Improving Trotter-Suzuki Decompositions with Higher-Order Schemes
Building Trust in Multi-Robot Systems through Shared Mental Models
Computer Science, Computer Vision and Pattern Recognition
Unlocking Image-Text Synthesis: A Comprehensive Review
Computer Science, Multiagent Systems
Fast and Accurate Path Finding with Implicit Conflict-Based Search
Computer Science, Machine Learning
Improved Dictionary Formation for Efficient Geographic Routing in Mobile Ad-Hoc Networks
Computer Science, Machine Learning
Efficient Deep Neural Network Compression Techniques for Distributed Learning Systems
Computer Science, Computer Vision and Pattern Recognition
Enhancing Semantic Segmentation with Hybrid Geometric Primitives
Computer Science, Software Engineering
Addressing Threats to Validity in LLM-Based Software Engineering Research
Computer Science, Computer Vision and Pattern Recognition