Improving Just Walk Out technology with multimodal AI
Since its launch in 2018, amazon’s Just Walk Out technology has transformed the shopping experience by allowing customers to enter ...
Tag: Improving
Trust-Align: An AI Framework for Improving the Reliability of Recall-Augmented Generation in Large Language Models
Large language models (LLMs) have gained significant attention due to their potential to improve various ai applications, particularly in natural ...
Improving large language models with diverse instructional data: A clustering and iterative refinement approach
Large language models (LLMs) have become a fundamental part of artificial intelligence, as they enable systems to understand, generate, and ...
Improving collaboration in the Master of Laws to achieve smarter, more efficient solutions | MIT News
Have you ever been asked a question to which you only knew part of the answer? To give a more ...
Stanford researchers present EntiGraph: a new machine learning method for generating synthetic data and improving the performance of language models in specialized domains
artificial intelligence (ai) has made great strides in recent years, especially with the development of large-scale language models. These models, ...
SaRA: A memory-efficient fine-tuning method for improving pre-trained diffusion models
Recent advances in diffusion models have significantly improved tasks such as image, video, and 3D generation, with pre-trained models such ...
Agent Workflow Memory (AWM): An AI method for improving the adaptability and efficiency of web browsing agents
Web browsing agents are based on the creation of autonomous systems capable of performing tasks such as searching, purchasing, and ...
Improving 3D reconstruction of sparse views with LM-Gaussian: leveraging large model priors for high-quality scene synthesis from limited images
Recent advances in sparse-view 3D reconstruction have focused on new view synthesis and scene representation techniques. Methods such as Neural ...
TempoKGAT: Improving temporal graph analysis with time-decreasing weights and selective neighbor aggregation
GNNs have excelled in analyzing structured data, but they face challenges with dynamic and temporal graphs. Traditional forecasting, often used ...
Improving diagnostic accuracy in LLMs with RuleAlign: a case study using the UrologyRD dataset
LLMs such as GPT-4, MedPaLM-2, and Med-Gemini perform well on medical parameters but need help to replicate the diagnostic skills ...
