Stanford researchers propose SleepFM: a new multimodal basic model for sleep analysis
Sleep medicine is a fundamental field that involves monitoring and evaluating physiological signals to diagnose sleep disorders and understand sleep ...
Tag: Stanford
5 free AI courses at Stanford
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Stanford Researchers Introduce SUQL: A Formal Query Language for Integrating Structured and Unstructured Data
Large language models (LLMs) have gained ground for their exceptional performance on various tasks. Recent research aims to improve its ...
Stanford University Researchers Introduce Octopus v2: Powering On-Device Language Models for Superagent Functionality
A critical challenge in artificial intelligence, specifically as it relates to large language models (LLMs), is balancing model performance and ...
A collection of free data science courses from Harvard, Stanford, MIT, Cornell, and Berkeley
Image by author Free courses are very popular on our platform and we have received many requests from both beginners ...
Stanford and Google AI researchers introduce MELON: an AI technique that can determine object-centered camera poses completely from scratch while reconstructing the object in 3D
While humans can easily infer the shape of an object from 2D images, computers have difficulty reconstructing accurate 3D models ...
This Stanford AI research looks at tracking and recovering the cause of the query
In a recent study, a team of researchers addressed the intrinsic drawbacks of current online content portals that allow users ...
Charting New Frontiers: Pioneering Stanford University Study on Geographic Bias in AI
The issue of bias in LLMs is a critical concern as these models, integral to advances in sectors such as ...
This AI paper from Stanford and Google DeepMind reveals how efficient exploration increases the effectiveness of human feedback to improve large language models
artificial intelligence has seen notable advances with the development of large language models (LLM). Thanks to techniques such as reinforcement ...
Stanford researchers present RAPTOR: a novel tree-based retrieval system that augments parametric knowledge of LLMs with contextual information
Augmented retrieval language models often retrieve only short fragments of a corpus, limiting the overall context of the document. This ...
