Hugging Face launches benchmark to test generative AI in health tasks
Generative ai models are increasingly being incorporated into healthcare environments, in some cases perhaps prematurely. Early adopters believe they will ...
Tag: tasks
LM-Guided CoT: A Novel Machine Learning Framework Leveraging a Lightweight (10B) LM in reasoning tasks
Chain of thought (CoT) stimulation involves instructing language models (LMs) to reason step by step, resulting in improved performance in ...
UniLLMRec: A comprehensive LLM-focused recommendation framework for executing multi-stage recommendation tasks across a recommendation chain
The goal of recommender systems is to predict user preferences based on historical data. Mainly, they are designed in sequential ...
Meet Plandex: An Open Source Terminal-Based AI Coding Engine for Complex Tasks
The field of software development is rapidly evolving and the integration of artificial intelligence (ai) with coding practices is set ...
Researchers at MIT and Harvard developed UNITS: a unified machine learning model for time series analysis that supports a universal task specification across multiple tasks
Time series analysis is essential in finance, healthcare, and environmental monitoring. This area faces a substantial challenge: the heterogeneity of ...
How to generate synthetic images for object detection tasks | by Dr. León Eversberg | March 2024
A step by step tutorial using Blender, Python and 3D AssetsImage created by the author.Not having enough training data is ...
What can CLIP learn from experts on specific tasks?
This article has been accepted into the UniReps Workshop at NeurIPS 2023. Contrastive language image pretraining has become the standard ...
Google AI introduces VideoPrism: a general-purpose video encoder that addresses various video understanding tasks with a single frozen model
Google researchers address the challenges of achieving a comprehensive understanding of diverse video content by introducing a novel encoder model, ...
This AI paper proposes a basic interactive agent model that uses a new multitasking agent training paradigm to train AI agents on a wide range of domains, data sets, and tasks.
ai development is moving from static task-focused models to dynamic and adaptive agent-based systems suitable for various applications. ai systems ...
This AI article presents Find+Replace Transformers: a family of multi-transformer architectures that can probably do things that no transformer can do alone and that outperform GPT-4 in several tasks
In the annals of computing history, the journey from early mechanical calculators to Turing Complete machines has been revolutionary. While ...
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