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, Human-Computer Interaction
Enhancing Caption Quality for Fair Technical Evaluations
Computer Science, Computer Vision and Pattern Recognition
Generating High-Quality Calligraphy Images with Conditional GANs
Computer Science, Machine Learning
Collaborative Bandit Algorithms: Exact Regret Bounds and Beyond
Computer Science, Computer Vision and Pattern Recognition
Exploring the Intersection of Deep Learning and Knowledge Graphs
Computer Science, Software Engineering
Improving Decision-Making Algorithms through Iterative Search and Refining Existing Works
Computer Science, Machine Learning
Fusing Multiple Views Improves Region Embedding for Land Use Clustering and Popularity Prediction
Computer Science, Computer Vision and Pattern Recognition
Generative AI-Driven 3D Representations: A New Frontier in Artificial Intelligence
Computer Science, Information Retrieval
Context-Aware Sequential Model for Multi-Behaviour Recommendation
Computer Science, Software Engineering
Strengthening Reliability in Smart Contract Analysis: A Dual-Author Approach
Computer Science, Human-Computer Interaction
Unconventional Visibility Solutions: Bodily Interactions with Drones
Computer Science, Machine Learning
Efficient Data Subset Selection for Continual Learning Under Concept Drift
Artificial Intelligence, Computer Science
Training Optimal Large Language Models: A Comparative Study
Artificial Intelligence, Computer Science
Analyzing Granularity and Refinement Step Length for Reinforcement Learning
Artificial Intelligence, Computer Science
Formal Framework for Normative Requirements Elicitation: Avoiding Ambiguity through Disambiguation
Computer Science, Neural and Evolutionary Computing
Optimization Methods for Machine Learning
Computer Science, Machine Learning
Optimizing Graph Topology for Improved Performance in Graph Neural Networks
Computer Science, Computer Vision and Pattern Recognition
Generalized Zero-Shot Learning: A Comprehensive Review
Computer Science, Networking and Internet Architecture
Synchronization Solutions for Industry 4.0: Minimizing Complexity and Costs
Computer Science, Information Retrieval