NPR's Scott Detrow speaks with Shane Littrell of Cornell University, whose new study concludes that those who buy into corporate jargon may actually be worse at their jobs.
See how passage-level retrieval works and why answer-first, well-structured content is more likely to be surfaced and reused.
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A Cornell Researcher Built a Corporate 'BS' Detector—Here's What It Reveals About Your Workplace
A new Cornell University study finds that employees who are impressed by corporate jargon score worse on decision-making ...
Abstract: Imbalanced data remains a challenge in classification research and significantly influences classifier performance. The strategy that is widely used to address this issue is the data-level ...
Objective Postmarketing safety data of avacopan, the first Food and Drug Administration (FDA) approved drug in a decade for ...
Background Hypertrophic cardiomyopathy (HCM) is associated with an increased risk of sudden cardiac death (SCD), and ...
Background Transcatheter aortic valve replacement (TAVR) has increasingly emerged as one of the primary treatments for ...
This repository is a comprehensive collection of Jupyter Notebooks designed to demonstrate and explore advanced Machine Learning algorithms and AI models. It serves as a practical resource for ...
Dominant edge direction based fast parameter estimation algorithm for sample adaptive offset in HEVC
Abstract: In this paper, we present the fast parameter estimation algorithm for sample adaptive offset (SAO) in High Efficiency Video Coding (HEVC). The main idea of a proposed method is to simplify ...
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