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Understanding A3B2: Adaptive Asymmetric Adapters for Few-Shot Vision-Language Classification Understanding A3B2: Adaptive Asymmetric Adapters for Few-Shot Vision-Language Classification
A technical explanation of A3B2, covering few-shot CLIP adaptation, branch bias, asymmetric text-image adapters, uncertainty-aware adapter dampening, load-balanced mixture-of-experts adapters, evaluation protocols, and key empirical findings.
2026-07-07
Understanding InherNet: Neural Network Inheritance Beyond Student Distillation Understanding InherNet: Neural Network Inheritance Beyond Student Distillation
A technical explanation of InherNet, covering neural network inheritance, model compression, SVD-based knowledge inheritance, asymmetric low-rank structure, gating fusion, and the main experimental takeaways.
2026-06-24
Understanding TLV-CoRe: Collaborative Representation Learning for Tactile-Language-Vision Alignment Understanding TLV-CoRe: Collaborative Representation Learning for Tactile-Language-Vision Alignment
A technical explanation of TLV-CoRe, covering tactile-language-vision alignment, sensor-agnostic tactile representation learning, Sensor-Aware Modulation, tactile-irrelevant decoupling, Unified Bridging Adapters, contrastive learning, RSS evaluation, and key empirical findings.
2026-06-16
Understanding PSMGD: Fast Multi-Objective Optimization with Periodic Gradient Weights Understanding PSMGD: Fast Multi-Objective Optimization with Periodic Gradient Weights
A technical explanation of PSMGD, covering multi-objective optimization, gradient conflict, periodic stochastic multi-gradient descent, convergence intuition, backpropagation complexity, and key empirical findings.
2026-06-04
Speaking the Language of Probability: From Classifier Evaluation to Generative Classifiers Speaking the Language of Probability: From Classifier Evaluation to Generative Classifiers
Study notes connecting classifier accuracy, confusion matrices, precision, recall, ROC/AUC, PR curves, calibration, cost-sensitive thresholds, generative classifiers, Gaussian class-conditional models, sigmoid/softmax, LDA, and QDA.
2025-10-30
DL study DL study
Notes on revisiting machine learning and deep learning with Dive into Deep Learning, PyTorch and conda setup, GPU environments, and ART/WiFi adversarial robustness tooling.
2023-03-01
Tiny AI stories Tiny AI stories
Personal notes on early ChatGPT and AI-tool experiences, including learning advice, coding productivity, academic writing, debugging, and end-to-end ML assignment workflows.
2022-12-09
CNN in Deep Learning: From Pixels to Feature Maps CNN in Deep Learning: From Pixels to Feature Maps
A beginner-friendly study note on convolutional neural networks, covering image tensors, convolution filters, feature maps, receptive fields, pooling, softmax, cross-entropy, and why CNNs work in deep learning.
2022-10-06
Git & GitHub Git & GitHub
A practical Git and GitHub command notebook covering clone, init, add, commit, log, checkout, reset, branch, merge, push, pull, and common remote-push troubleshooting.
2022-09-29
How to build your own website How to build your own website
A running note on building and maintaining this Hexo + GitHub Pages website, including setup links, common bugs, Hexo commands, deployment flow, image handling, Markdown, and LaTeX tips.
2022-09-19