NEWSLETTER
Flextok: Folding in token sequences 1d flexible length
This work was carried out in collaboration with the Federal Swiss Institute of Lausanian technology (EPFL). The tokenization of images ...
Tag: sequences
EMOTION: Generation of expressive movement sequences for humanoid robots with in-context learning
This paper presents a framework, called EMOTION, for generating expressive movement sequences in humanoid robots, improving their ability to engage ...
Writer researchers present Writing in the Margins (WiM): a new inference pattern for large language models designed to optimize the handling of long input sequences in retrieval-oriented tasks
artificial intelligence (ai) and natural language processing (NLP) have seen significant advances in recent years, particularly in the development and ...
Idefics3-8B-Llama3 is released: an open multimodal model that accepts arbitrary sequences of image and text inputs and produces text outputs
Machine learning models that integrate text and images have become critical to improving capabilities in various applications. These multimodal models ...
TiTok: an innovative AI method to tokenize images into 1D latent sequences
In recent years, imaging has made significant progress due to advances in both transformers and diffusion models. Similar to trends ...
BurstAttention: An innovative machine learning framework that transforms efficiency in large language models with an advanced distributed attention mechanism for extremely long sequences
Large language models (LLMs) have revolutionized the way computers understand and generate human language in machine learning and natural language ...
Stanford University researchers present FlashFFTConv: a new artificial intelligence system to optimize FFT convolutions for long sequences
Reasoning efficiently through extended sequences is a major difficulty in machine learning. Recently, convolutions have emerged as a critical primitive ...
