Paper Bites
Each Paper Bite is a focused Markdown note: why the paper matters, the core idea, how it works, what to inspect in the results, and practical takeaways.
Chain-of-Zoom treats extreme super-resolution as a sequence of zoom steps, using multi-scale prompts and preference alignment to guide details beyond a model's usual scale range.
LoRA freezes a pretrained language model and learns small low-rank update matrices, making task adaptation much cheaper to train, store, and switch.
ControlNet adds spatial conditioning to pretrained text-to-image diffusion models while protecting the original model's generation quality through zero-initialized control branches.
ViT-CoMer keeps the flexibility of a plain Vision Transformer, then adds a parallel convolutional branch so dense prediction tasks can use richer multi-scale features.