This research delves into the current literature on bias in Natural Language Processing Models and the techniques proposed to mitigate the problem of bias, including why it is important to tackle bias...
Large Language Models (LLMs) such as GPT-3.5, Bard, and Claude exhibit applicability across numerous tasks. One domain of interest is their use in algorithmic hiring, specifically in matching resumes ...
We present both the Lucie Training Dataset and the Lucie-7B foundation model. The Lucie Training Dataset is a multilingual collection of textual corpora centered around French and designed to offset a...
Hey there, looking for the status of Presidency in 2025. How's the student life, hostel life, sports, extra and anything special.Try to give unbiased comments, ground level reviews
Thanks in advance ...
Cyberspace is an ever-evolving battleground involving adversaries seeking to circumvent existing safeguards and defenders aiming to stay one step ahead by predicting and mitigating the next threat. Ex...
We present a system for the prediction of microsatellite instability (MSI) from H&E images of colorectal cancer using deep learning (DL) techniques customized for tissue microarrays (TMAs). The system...
Seraphim was founded in 2011 with the aim of consistently providing relevant and unbiased information on every exclusive item presented at the sales and mainstore locations most desired by Seraphim ...
The accuracy of deep neural networks is significantly affected by how well mini-batches are constructed during the training step. In this paper, we propose a novel adaptive batch selection algorithm c...
Spider-Man: Far From Home - When Mysterio laments how Iron Man treated his nanotechnology as a joke we get a flashback to Captain America: Civil War when Tony had the presentation for the technology, ...
At age two, humans are just learning to speak, and they see the world in an unbiased way. At age two, the COMPLETE (COordinated Molecular Probe Line Extinction Thermal Emission) Survey of Star-Forming...
This paper introduces a quantile regression estimator for panel data models with individual heterogeneity and attrition. The method is motivated by the fact that attrition bias is often encountered in...
Most cost-benefit analyses assume that the estimates of costs and benefits are more or less accurate and unbiased. But what if, in reality, estimates are highly inaccurate and biased? Then the assumpt...
**I am NOT OOP, OOP is** u/stomatella
**Originally posted to r/relationships**
**My boyfriend (M25) and I (F23) had an argument that is giving me red flags. Is it enough to leave our years long rela...
1 day ago · MightyTips offers you a fantastic range of online sports betting tips, odds comparison, and betting predictions for football, basketball, and other sports. Fully independent & unbiased s...
Perceptual speech quality is an important performance metric for teleconferencing applications. The mean opinion score (MOS) is standardized for the perceptual evaluation of speech quality and is obta...
We introduce the Graded Transformer framework, a new class of sequence models that embeds algebraic inductive biases through grading transformations on vector spaces. Extending Graded Neural Networks ...
Context. In Gaia era, atmospheric turbulence, which causes stochastic wander of a star image, is a fundamental limitation to the astrometric accuracy of ground-based optical imaging. However, the posi...
This work proposes to analyse some keywords for bias analysis. For this, we are using several NLP approaches and compare them based on their capability of detecting keywords to analyse bias. The overa...
