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.
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Learning Regular Sets from Queries and Counterexamples
Quantitative Biology, Quantitative Methods
Harnessing AI for Biological Data Analysis: Efficient Generation of Q&A Pairs
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Training a Processor to Minimize Distance in Encoded Data
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Unraveling the Mysteries of Language: Quantifiers and Atypical Words
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Semantic Segmentation: A Comprehensive Review of Recent Approaches
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Auto-Encoding Variational Bayes
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Compiling Propositional Logic to Decomposable Negation Normal Form
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Semi-Supervised OCT Fluid Segmentation with Label Denoising
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Neural Graphics Primitives: A New Frontier in Image Generation
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Improving Model Performance through Contextual Features: An Ablation Study
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Uncovering Hidden Failures in Text-to-Image Synthesis: A Closer Look at CLIP
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Comparative Analysis of Time-Contrastive Networks and Self-Supervised Learning Methods for Fine-Grained Human Activity Understanding
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Machine Learning for Code Analysis and Optimization
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Few-Shot Learning: A Comprehensive Review of Recent Approaches and Techniques
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Improving Hyperdimensional Computing for Efficient Speech Recognition
Computer Science, Programming Languages
Natural Language Libraries for Code Generation
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