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.
Computer Science, Hardware Architecture
In-Memory Computing: The Future of Energy-Efficient and High-Throughput AI Processing
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Efficient Voxel-as-Point Point Cloud Segmentation
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Fast and Accurate Subset Sampling via Rapidly Mixing Markov Chains
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Adaptive Parameter-State Estimation for Nonlinear Systems with Uncertain Parameters
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Unconventional Approach to Rendering Quality: Trading Mesh Complexity for Color Field Accuracy
Enhancing Autonomous Vehicle Decision-Making with Game Theory and Interaction Orientation Identification
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Algorithmic Initiation of Interactive ML Systems for Diverse Users
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Fast Image Segmentation via Novel Variational Active Contour Model
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Refining Pre-Existing Graph Convolutional Networks with Locked Transformers
Electrical Engineering and Systems Science, Systems and Control
Formation Maneuver Control of Mobile Agents Under Time-Varying Conditions
Computation and Language, Computer Science
Studying Translation Difficulty: A Review of Empirical Research
Computer Science, Information Theory
Computing the Capacity of an Erasure Channel with Non-Zero Probability
Computer Science, Computer Vision and Pattern Recognition
Pivotal Tuning for Latent-Based Image Editing
Computer Science, Machine Learning
Machine Learning for Portfolio Optimization: A Comparative Study of GNNs and GATs
Mathematics, Optimization and Control
Distributed Optimization Algorithms: A Comparative Study
Computer Science, Machine Learning
Simplicial Network Processing: A New Frontier in Graph Signal Processing
Computer Science, Machine Learning
Improving Data Dependence Estimation in Markov Decision Processes via Weak Dependence
Artificial Intelligence, Computer Science