Generalizable autoregressive modeling of time series through functional narratives
Time series data are inherently functions of time, however current transformers often learn time series by modeling them as mere ...
Tag: Generalizable
Generalizable error modeling for human data annotation: Evidence from an industrial-scale search data annotation program.
Machine learning (ML) and artificial intelligence (ai) systems rely heavily on human-annotated data for training and evaluation. A major challenge ...
Large language models as generalizable policies for built-in tasks
We show that large language models (LLMs) can be tailored to be generalizable policies for embodied visual tasks. Our approach, ...
LUMOS: An Open Source Generalizable Language Agent Training Framework
Imagine having a digital assistant that can not only answer your questions but also navigate the web, solve complex math ...
GeFF: Revolutionizing robot perception and action with scene-level generalizable neural feature fields
When a buzzing noise catches your attention, you're walking down the bustling city street, carefully holding your morning coffee. Suddenly, ...
This machine learning research presents Premier-TACO: a robust and highly generalizable representation pretraining framework for low-shot policy learning.
In our ever-evolving world, the importance of sequential decision making (SDM) in machine learning cannot be underestimated. Unlike static tasks, ...
Alibaba Announces RichDreamer: A Generalizable Normal Depth Diffusion Model for Richness of Detail in Text to 3D
In the context of text-to-3D conversion, the key challenge lies in bringing 2D diffusion to 3D generation. Existing methods face ...
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