Artificial Intelligence l l AI Updates
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News about AI & DL & ML!!! Admin: @Gayrat_Tangriberganov
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❇️ Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization
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❇️ Expanding the Horizon for Surround-view 3D Object Detection
#ObjectDetection
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❇️ Semantic Line Combination Detection
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❇️ Recursive Video Lane Detection
#LaneDetection
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❇️ MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
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❇️ Face Adapter for Pre-Trained Diffusion Models with Fine-Grained ID and Attribute Control
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❇️ MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities
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❇️ ⚽️ COMPUTER VISION & SPORT ⚽️
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❇️ TACO: (Topics in Algorithmic COde generation dataset)
💥 Larger scale: TACO includes a training set (25,443 problems) and a test set (1,000 problems), making it the largest code generation dataset currently available.
💥 Higher quality: Each problem in the TACO dataset is designed to match a diverse set of solution answers, with answer sizes of up to 1.55M. This ensures that the model is not prone to overfitting during training and validates the effectiveness of evaluation results.
💥 Fine-grained labels: Each problem in the TACO dataset includes fine-grained labels such as task topics, algorithms, skills, and difficulty levels. These labels provide more accurate references for the training and evaluation of code generation models.
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❇️ R2E: Turning any GITHUB Repository into a
Programming Agent Environment
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❇️ Video Loopback for WebUI
#webui #LoRA
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❇️ ort is an (unofficial) ONNX Runtime 1.17 wrapper for Rust based on the now inactive onnxruntime-rs. ONNX Runtime accelerates ML inference on both CPU & GPU.
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❇️ Anyline: A Fast, Accurate, and Detailed Line Detection Preprocessor
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❇️ ViViD: Video Virtual Try-on using Diffusion Models
#Diffusion
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❇️ A Native-PyTorch Library for LLM Fine-tuning
#LLMs #FineTuning
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❇️ The Platonic Representation Hypothesis
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❇️ ChartAssisstant: A Universal Chart Multimodal Language Model via Chart-to-Table Pre-training and Multitask Instruction Tuning
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🧠📚 𝐋𝐢𝐧𝐞𝐚𝐫 𝐀𝐥𝐠𝐞𝐛𝐫𝐚 𝐈 - 𝐋𝐞𝐜𝐭𝐮𝐫𝐞 𝐍𝐨𝐭𝐞𝐬, 𝐌𝐀𝐓𝐇 𝟐𝟑𝟑 🚀⚡️ - a cool #linearalgebra course by Cesar O. Aguilaron
𝕿𝖆𝖇𝖑𝖊 𝖔𝖋 𝕮𝖔𝖓𝖙𝖊𝖓𝖙𝖘:
🎯 Systems of Linear Equations
🎯 Row Reduction and Echelon Forms
🎯 Vector Equations The Matrix Equation Ax = b
🎯 Homogeneous and Nonhomogeneous Systems
🎯 Linear Independence
🎯 Introduction to Linear Mappings
🎯 Onto, One-to-One, and Standard Matrix
🎯 Matrix Algebra
🎯 Invertible Matrices
🎯 Determinants
🎯 Properties of the Determinant
🎯 Applications of the Determinant
🎯 Vector Spaces
🎯 Linear Maps
🎯 Linear Independence, Bases, and Dimension
🎯 The Rank Theorem
🎯 Coordinate Systems
🎯 Change of Basis
🎯 Inner Products and Orthogonality
🎯 Eigenvalues and Eigenvectors
🎯 The Characteristic Polynomial
🎯 Diagonalization
🎯 Diagonalization of Symmetric Matrices
🎯 The PageRank Algortihm
🎯 Discrete Dynamical Systems
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❇️ ClickDiffusion: Harnessing LLMs for Interactive Precise Image Editing
#Diffusion #LLMs
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