Trending Research
Rewrite the Stars
Recent studies have drawn attention to the untapped potential of the "star operation" (element-wise multiplication) in network design.
QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving
The key insight driving QServe is that the efficiency of LLM serving on GPUs is critically influenced by operations on low-throughput CUDA cores.
DocRes: A Generalist Model Toward Unifying Document Image Restoration Tasks
This underscores the potential of DocRes across a broader spectrum of document image restoration tasks.
WavCraft: Audio Editing and Generation with Large Language Models
We introduce WavCraft, a collective system that leverages large language models (LLMs) to connect diverse task-specific models for audio content creation and editing.
FeatUp: A Model-Agnostic Framework for Features at Any Resolution
Deep features are a cornerstone of computer vision research, capturing image semantics and enabling the community to solve downstream tasks even in the zero- or few-shot regime.
Ranked #1 on
Feature Upsampling
on ImageNet
PuLID: Pure and Lightning ID Customization via Contrastive Alignment
We propose Pure and Lightning ID customization (PuLID), a novel tuning-free ID customization method for text-to-image generation.
LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
We outperform encoder-only models by a large margin on word-level tasks and reach a new unsupervised state-of-the-art performance on the Massive Text Embeddings Benchmark (MTEB).
ThemeStation: Generating Theme-Aware 3D Assets from Few Exemplars
To this end, we design a two-stage framework that draws a concept image first, followed by a reference-informed 3D modeling stage.
Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models
We study how to apply large language models to write grounded and organized long-form articles from scratch, with comparable breadth and depth to Wikipedia pages.
AM-RADIO: Agglomerative Vision Foundation Model -- Reduce All Domains Into One
nvlabs/radio
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A handful of visual foundation models (VFMs) have recently emerged as the backbones for numerous downstream tasks.
