Trending Research
Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
mindspore-lab/mindone
•
•
None 2023
We then explore the impact of finetuning our base model on high-quality data and train a text-to-video model that is competitive with closed-source video generation.
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.
Autonomous LLM-driven research from data to human-verifiable research papers
As AI promises to accelerate scientific discovery, it remains unclear whether fully AI-driven research is possible and whether it can adhere to key scientific values, such as transparency, traceability and verifiability.
Improving Diffusion Models for Virtual Try-on
yisol/IDM-VTON
•
•
Finally, we present a customization method using a pair of person-garment images, which significantly improves fidelity and authenticity.
Ranked #1 on
Virtual Try-on
on VITON-HD
OS-Copilot: Towards Generalist Computer Agents with Self-Improvement
Autonomous interaction with the computer has been a longstanding challenge with great potential, and the recent proliferation of large language models (LLMs) has markedly accelerated progress in building digital agents.
KAN: Kolmogorov-Arnold Networks
Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs).
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.
TimeGPT-1
In this paper, we introduce TimeGPT, the first foundation model for time series, capable of generating accurate predictions for diverse datasets not seen during training.
Inf-DiT: Upsampling Any-Resolution Image with Memory-Efficient Diffusion Transformer
However, due to a quadratic increase in memory during generating ultra-high-resolution images (e. g. 4096*4096), the resolution of generated images is often limited to 1024*1024.
X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Molecular Design
Starting with a set of pre-trained LoRA adapters, our gating strategy uses the hidden states to dynamically mix adapted layers, allowing the resulting X-LoRA model to draw upon different capabilities and create never-before-used deep layer-wise combinations to solve tasks.
