activity
20232025
most citedMovie Gen: A Cast of Media Foundation Models

8 citations · 10 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2025

Dialect Normalization using Large Language Models and Morphological Rules

Antonios Dimakis, John Pavlopoulos, Antonios Anastasopoulos

Natural language understanding systems struggle with low-resource languages, including many dialects of high-resource ones. Dialect-to-standard normalization attempts to tackle thi…

cs.CL2024★ 1 cited

When Every Token Counts: Optimal Segmentation for Low-Resource Language Models

Bharath Raj, Garvit Suri, Vikrant Dewangan +1

Traditional greedy tokenization methods have been a critical step in Natural Language Processing (NLP), influencing how text is converted into tokens and directly impacting model p…

cs.CV2024★ 8 cited

Movie Gen: A Cast of Media Foundation Models

Adam Polyak, Amit Zohar, Andrew Brown +85

We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabili…

cs.AI2024

The Llama 3 Herd of Models

Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556

Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…

cs.CV2024

Layout Agnostic Scene Text Image Synthesis with Diffusion Models

Qilong Zhangli, Jindong Jiang, Di Liu +6

While diffusion models have significantly advanced the quality of image generation their capability to accurately and coherently render text within these images remains a substanti…

cs.CV2024

Towards Artwork Explanation in Large-scale Vision Language Models

Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2

Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…

cs.CV2024★ 1 cited

Animated Stickers: Bringing Stickers to Life with Video Diffusion

David Yan, Winnie Zhang, Luxin Zhang +15

We introduce animated stickers, a video diffusion model which generates an animation conditioned on a text prompt and static sticker image. Our model is built on top of the state-o…

cs.CV2023

Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression

Animesh Sinha, Bo Sun, Anmol Kalia +14

We introduce Style Tailoring, a recipe to finetune Latent Diffusion Models (LDMs) in a distinct domain with high visual quality, prompt alignment and scene diversity. We choose sti…

cs.CV2023

CiT: Curation in Training for Effective Vision-Language Data

Hu Xu, Saining Xie, Po-Yao Huang +5

Large vision-language models are generally applicable to many downstream tasks, but come at an exorbitant training cost that only large institutions can afford. This paper trades g…