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ViBT: The Beginning of Noise-Free Generation, Vision Bridge Transformer (Paper Review)
Analyzing ViBT's core technology and performance that transforms images/videos without noise using a Vision-to-Vision paradigm with Brownian Bridge.
SteadyDancer Complete Analysis: A New Paradigm for Human Image Animation with First-Frame Preservation
Make a photo dance - why existing methods fail and how SteadyDancer solves the identity problem by guaranteeing first-frame preservation through the I2V paradigm.
Still Using GPT-4o for Everything? (How to Build an AI Orchestra & Save 90%)
An 8B model as conductor routes queries to specialized experts based on difficulty. ToolOrchestra achieves GPT-4o performance at 1/10th the cost using a Compound AI System approach.
BPE vs Byte-level Tokenization: Why LLMs Struggle with Counting
Why do LLMs fail at counting letters in "strawberry"? The answer lies in tokenization. Learn how BPE creates variable granularity that hides character structure from models.
The Real Bottleneck in RAG Systems: It's Not the Vector DB, It's Your 1:N Relationships
Many teams try to solve RAG accuracy problems by tuning their vector database. But the real bottleneck is chunking that ignores the relational structure of source data.
"Can SQL Do This?" โ Escaping Subquery Hell with Window Functions
LAG, LEAD, RANK for month-over-month, rankings, and running totals
One Wrong JOIN and Your Revenue Doubles โ The Complete Guide to Accurate Revenue Aggregation
Row Explosion in 1:N JOINs and how to aggregate revenue correctly
Why Does Your SQL Query Take 10 Minutes? โ From EXPLAIN QUERY PLAN to Index Design
EXPLAIN, indexes, WHERE vs HAVING โ diagnose and optimize slow queries yourself
SANA: O(nยฒ)โO(n) Linear Attention Generates 1024ยฒ Images in 0.6 Seconds
How Linear Attention solved Self-Attention quadratic complexity. The secret behind 100x faster generation compared to DiT.
PixArt-ฮฑ: How to Cut Stable Diffusion Training Cost from $600K to $26K
23x training efficiency through Decomposed Training strategy. Making Text-to-Image models accessible to academic researchers.
DiT: Replacing U-Net with Transformer Finally Made Scaling Laws Work (Sora Foundation)
U-Net shows diminishing returns when scaled up. DiT improves consistently with size. Complete analysis of the architecture behind Sora.
From 512ร512 to 1024ร1024: How Latent Diffusion Broke the Resolution Barrier
How Latent Space solved the memory explosion problem of pixel-space diffusion. Complete analysis from VAE compression to Stable Diffusion architecture.
DDIM: 20x Faster Diffusion Sampling with Zero Quality Loss (1000โ50 Steps)
Use your DDPM pretrained model as-is but sample 20x faster. Mathematical derivation of probabilisticโdeterministic conversion and eta parameter tuning.
DDPM Math Walkthrough: Deriving Forward/Reverse Process Step by Step
Generate high-quality images without GAN mode collapse. Derive every equation from ฮฒ schedule to loss function and truly understand how DDPM works.
Why Your Translation Model Fails on Long Sentences: Context Vector Bottleneck Explained
BLEU score drops by half when sentences exceed 40 words. Deep analysis from information theory and gradient flow perspectives, proving why Attention is necessary.
Bahdanau vs Luong Attention: Which One Should You Actually Use? (Spoiler: Luong)
Experimental comparison of additive vs multiplicative attention performance and speed. Why Luong is preferred in production, proven with code.
Building Seq2Seq from Scratch: How the First Neural Architecture Solved Variable-Length I/O
How Encoder-Decoder architecture solved the fixed-size limitation of traditional neural networks. From mathematical foundations to PyTorch implementation.
AdamW vs Lion: Save 33% GPU Memory While Keeping the Same Performance
How Lion optimizer saves 33% memory compared to AdamW, and the hyperparameter tuning guide for real-world application. Use it wrong and you lose.