Remove Data Scarcity Remove Machine Learning Remove NLP
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Innovations in Analytics: Elevating Data Quality with GenAI

Towards AI

By leveraging GenAI, we can streamline and automate data-cleaning processes: Clean data to use AI? Clean data through GenAI! Three ways to use GenAI for better data Improving data quality can make it easier to apply machine learning and AI to analytics projects and answer business questions.

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Advancing Cantonese NLP: Bridging Development Gaps in Large Language Models with New Benchmarks and Open-Source Innovations

Marktechpost

Large language models (LLMs) have revolutionized natural language processing (NLP), particularly for English and other data-rich languages. The scarcity of training data and benchmarks for Cantonese LLMs further complicates development efforts.

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Innovation in Synthetic Data Generation: Building Foundation Models for Specific Languages

Unite.AI

Synthetic data , artificially generated to mimic real data, plays a crucial role in various applications, including machine learning , data analysis , testing, and privacy protection. However, generating synthetic data for NLP is non-trivial, demanding high linguistic knowledge, creativity, and diversity.

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Award-Winning Breakthroughs at NeurIPS 2023: A Focus on Language Model Innovations

Topbots

Privacy Auditing with One (1) Training Run By Thomas Steinke , Milad Nasr , and Matthew Jagielski from Google This research paper introduces a novel method for auditing differentially private (DP) machine learning systems using just a single training run. The paper also explores alternative strategies to mitigate data scarcity.

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This AI Paper Proposes a Novel Bayesian Deep Learning Model with Kernel Dropout Designed to Enhance the Reliability of Predictions in Medical Text Classification Tasks

Marktechpost

This scarcity challenges the AI’s ability to learn effectively and deliver reliable results, which is critical when these outcomes directly affect patient care. Advanced NLP techniques improve Electronic Health Records management, facilitating the extraction of valuable information.

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Meet AnomalyGPT: A Novel IAD Approach Based on Large Vision-Language Models (LVLM) to Detect Industrial Anomalies

Marktechpost

On various Natural Language Processing (NLP) tasks, Large Language Models (LLMs) such as GPT-3.5 With just a few normal samples, AnomalyGPT can also learn in context, allowing for quick adjustment to new objects. They optimize the LVLM using synthesized anomalous visual-textual data and incorporating IAD expertise.

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Achieving accurate image segmentation with limited data: strategies and techniques

deepsense.ai

Supervised learning Supervised learning is a widely used approach in machine learning, where algorithms are trained using a large number of input examples paired with their corresponding expected outputs. SegGPT Many successful approaches from NLP are now being translated into computer vision. Source: own study.