#flow-matching
9 articles
01
·★ MEMBER·PAPER·9 min read
Paper Walkthrough: LLaDA-Image — Building the Visual Prior from Images Alone, Then Distilling to 2–4 Steps
A training recipe that builds the visual prior from images alone before any caption enters the picture. We walk through LLaDA-Image — a 6B DiT trained from scratch and distilled down to 2–4 sampling steps — following the design decisions the paper actually makes.
02
·Agents·★ MEMBER·PAPER·12 min read
Paper Walkthrough: ZimaBlue — Turning 120,000 Hours of Egocentric Video into Robot Skill
A ground-up walkthrough of the World Action Model that converts 120,000 hours of action-free egocentric video into robot control: a three-stage curriculum, a 100-D unified action interface, and an asynchronous Slow-Fast pair that takes zero-shot success from 36.1% to 77.8% at a 33 ms control loop.
03
·★ MEMBER·PAPER·12 min read
Paper walkthrough: Qwen-Drive-1.0 — bolting 3D perception and planning onto a VLM without touching its architecture
Leave the pretrained VLM exactly as it is, attach a BEV perception head and a Planning Expert, and you get 3D detection, occupancy, maps and trajectory generation in one model — general vision-language ability nearly intact, 90.7 PDMS on NAVSIM. A ground-up walkthrough, straight from the paper.
04
·★ MEMBER·PAPER·14 min read
Paper Walkthrough: DreamX-Creator — Making Sound and Picture Together in 7B, Then Finishing at 2K in One Step
A ground-up walkthrough of a 7B model that denoises audio and video inside one generative process: the gated cross-modal attention, the modality-aware reinforcement learning, the one-step 2K refiner — and the unusually heavy caveats the authors put on their own results.
05
·★ MEMBER·PAPER·13 min read
Paper Walkthrough: GameWAM — Generating the Next Frame and the Next Keystroke Together
A ground-up walkthrough of the first World–Action Model for native closed-loop game and GUI control: how it plans 16 actions but commits only 8, and how low-frequency noise in the sampled action source quietly spins the camera.
06
·Inference & Serving·★ MEMBER·PAPER·13 min read
Paper explained: Self-OPD — an image generator that distills itself, with no teacher
No teacher model at all: at every denoising step the student spawns K copies of itself, scores them, and pulls toward the good branches while pushing away from the bad ones. A ground-up walkthrough of Self-OPD, an alignment method for flow matching image generators.
07
·Generative Models·★ MEMBER·PAPER·10 min read
Flow Matching from Scratch — What Came After Diffusion, and Why It Goes Straight
Flow matching — the formulation underneath Stable Diffusion 3 and FLUX — explained with no prerequisites. Velocity fields, ODEs, and rectified flow, told through analogy and interactive figures, all the way to the scheduler settings you actually touch in production.
08
·Audio & Speech·★ MEMBER·PAPER·10 min read
Paper Walkthrough: SwanTale — Designing Voices from Words Alone, with Speech and Sound in One Waveform
ByteDance's SwanTale handles two jobs in one model: cloning a voice from reference audio (zero-shot) and building voices, ambience, and sound effects purely from a natural-language caption (instruct). We walk through the paper, from the 70M-caption data pipeline to Unified MoE routing and GRPO post-training.
09
·★ MEMBER·PAPER·9 min read
Paper Walkthrough: AURORA-LM — A Diffusion Language Model That Keeps Its Text Latent Full-Width Instead of Compressing It
A walkthrough of AURORA-LM, a continuous-latent diffusion language model that rejects the usual compromise of compressing text latents to make diffusion easier. It keeps a decodable, width-1024 latent and learns its distribution with a low-rank input pathway, width-calibrated noise, and self-trajectory consistency.