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Data Scarcity

Open Artificial Knowledge (OAK) Dataset: A Large-Scale Resource for AI Research Derived from Wikipedia’s Main Categories

Marktechpost

JULY 22, 2024

However, acquiring such datasets presents significant challenges, including data scarcity, privacy concerns, and high data collection and annotation costs. Artificial (synthetic) data has emerged as a promising solution to these challenges, offering a way to generate data that mimics real-world patterns and characteristics.

AI Researcher

AI Researcher AI Research Data Scarcity Prompt Engineer

NeoBERT: Modernizing Encoder Models for Enhanced Language Understanding

Marktechpost

MARCH 3, 2025

Data Scarcity: Pre-training on small datasets (e.g., All credit for this research goes to the researchers of this project. While newer models like GTE and CDE improved fine-tuning strategies for tasks like retrieval, they rely on outdated backbone architectures inherited from BERT.

BERT

BERT Data Scarcity Natural Language Processing Large Language Models

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The Intersection of AI and Sales: Personalization Without Compromise

How to Achieve High-Accuracy Results When Using LLMs

Relevance, Reach, Revenue: How to Turn Marketing Trends From Hype to High-Impact

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Trending Sources

AI Researchers At Mayo Clinic Introduce A Machine Learning-Based Method For Leveraging Diffusion Models To Construct A Multitask Brain Tumor Inpainting Algorithm

Marktechpost

JULY 23, 2023

Data scarcity and data imbalance are two of these challenges. This Article is written as a research summary article by Marktechpost Staff based on the research paper ' MULTITASK BRAIN TUMOR INPAINTING WITH DIFFUSION MODELS: A METHODOLOGICAL REPORT '. All Credit For This Research Goes To Researchers on This Project.

Machine Learning

Machine Learning Data Scarcity Algorithm AI Researcher

Webinars

The Intersection of AI and Sales: Personalization Without Compromise

How to Achieve High-Accuracy Results When Using LLMs

Relevance, Reach, Revenue: How to Turn Marketing Trends From Hype to High-Impact

MORE WEBINARS

Meta AI Researchers Introduce Token-Level Detective Reward Model (TLDR) to Provide Fine-Grained Annotations for Large Vision Language Models

Marktechpost

OCTOBER 26, 2024

To address data scarcity and granularity issues, the system employs sophisticated synthetic data generation techniques, particularly focusing on dense captioning and visual question-answering tasks. Don’t Forget to join our 55k+ ML SubReddit.

AI Researcher

AI Researcher AI Research Data Scarcity Inference Engine

Amazon AI Research Introduces BioBRIDGE: A Parameter-Efficient Machine Learning Framework to Bridge Independently Trained Unimodal Foundation Models to Establish Multimodal Behavior

Marktechpost

FEBRUARY 28, 2024

By aligning the embedding space of unimodal FMs through cross-modal transformation models utilizing KG triplets, BioBRIDGE maintains data sufficiency and efficiency and navigates the challenges posed by computational costs and data scarcity that hinder the scalability of multimodal approaches.

Machine Learning

Machine Learning AI Researcher AI Research Data Scarcity

Full Guide on LLM Synthetic Data Generation

Unite.AI

JULY 5, 2024

As the technology continues to evolve, it promises to unlock new possibilities in AI research and application development, while addressing critical challenges related to data scarcity and privacy.

LLM

LLM Prompt Engineer Prompt Engineering Data Scarcity

A New AI Research from China Proposes SHIP: A Plug-and-Play Generative AI Approach to Improve Existing Fine-Tuning Methods

Marktechpost

JULY 29, 2023

Overall, the paper presents a significant contribution to the field by addressing the challenge of data scarcity for certain classes and enhancing the performance of CLIP fine-tuning methods using synthesized data. All Credit For This Research Goes To the Researchers on This Project. Check out the Paper.

AI Researcher

AI Researcher AI Research Generative AI Data Scarcity

Meet LP-MusicCaps: A Tag-to-Pseudo Caption Generation Approach with Large Language Models to Address the Data Scarcity Issue in Automatic Music Captioning

Marktechpost

AUGUST 3, 2023

Also, don’t forget to join our 27k+ ML SubReddit , 40k+ Facebook Community, Discord Channel , and Email Newsletter , where we share the latest AI research news, cool AI projects, and more.

Data Scarcity

Data Scarcity Large Language Models BERT Natural Language Processing

This Paper Introduces TF-T2V: A Novel Text-to-Video Generation Framework with Impressive Scalability and Performance Improvements

Marktechpost

DECEMBER 30, 2023

link] To conclude, the TF-T2V framework offers several key advantages: It innovatively utilizes text-free videos, addressing the data scarcity issue prevalent in the field. All credit for this research goes to the researchers of this project. If you like our work, you will love our newsletter.

Data Scarcity

Data Scarcity Computer Vision Artificial Intelligence Artificial Intelligence

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

Marktechpost

SEPTEMBER 2, 2023

Researchers from Chinese Academy of Sciences, University of Chinese Academy of Sciences, Objecteye Inc., and Wuhan AI Research present AnomalyGPT, a unique IAD methodology based on LVLM, as shown in Figure 1, as neither existing IAD approaches nor LVLMs can adequately handle the IAD problem. Data scarcity is the first.

Data Scarcity

Data Scarcity Large Language Models Natural Language Processing LLM

This Paper Explores AI-Driven Hedging Strategies in Finance: A Deep Dive into the Use of Recurrent Neural Networks and k-Armed Bandit Models for Efficient Market Simulation and Risk Management

Marktechpost

DECEMBER 31, 2023

He highlighted the necessity for effective data use by stressing the significant amount of data many AI systems consume. Another researcher highlighted the challenge of considering AI model-free due to market data scarcity for training, particularly in realistic derivative markets.

Neural Network

Neural Network Data Scarcity Artificial Intelligence Artificial Intelligence

University of Cambridge Researchers Introduce a Dataset of 50,000 Synthetic and Photorealistic Foot Images along with a Novel AI Library for Foot

Marktechpost

NOVEMBER 9, 2023

They also make available a sizable collection of artificially photorealistic photos matched with ground truth labels for these kinds of signals to overcome data scarcity. All credit for this research goes to the researchers of this project. If you like our work, you will love our newsletter.

Data Scarcity

Data Scarcity Computer Vision AI AI

Data-Centric AI: The Importance of Systematically Engineering Training Data

Unite.AI

SEPTEMBER 12, 2024

Over the past decade, Artificial Intelligence (AI) has made significant advancements, leading to transformative changes across various industries, including healthcare and finance. Data scarcity is another significant issue. Gathering large volumes of labeled data in many fields is complicated, time-consuming, and costly.

Data Quality

Data Quality Data Scarcity AI AI

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

Topbots

DECEMBER 19, 2023

Generated with Midjourney The NeurIPS 2023 conference showcased a range of significant advancements in AI, with a particular focus on large language models (LLMs), reflecting current trends in AI research. These awards highlight the latest achievements and novel approaches in AI research. Enjoy this article?

Large Language Models

Large Language Models Natural Language Processing Machine Learning AI Researcher

ByteDance Researchers Introduce Tarsier2: A Large Vision-Language Model (LVLM) with 7B Parameters, Designed to Address the Core Challenges of Video Understanding

Marktechpost

JANUARY 15, 2025

Video understanding has long presented unique challenges for AI researchers. Conclusion Tarsier2 marks a significant step forward in video understanding by addressing key challenges such as temporal alignment, hallucination reduction, and data scarcity.

Data Scarcity

Data Scarcity Large Language Models AI Research AI Researcher

Few-Shot Preference Optimization (FSPO): A Novel Machine Learning Framework Designed to Model Diverse Sub-Populations in Preference Datasets to Elicit Personalization in Language Models for Open-Ended Question Answering

Marktechpost

MARCH 4, 2025

The approach generates over a million structured synthetic preferences to address data scarcity. Over 1M synthetic personalized preferences are generated to address data scarcity, ensuring diversity and consistency for effective real-world transfer. All credit for this research goes to the researchers of this project.

Machine Learning

Machine Learning Data Scarcity LLM OpenAI

A Comprehensive Guide to Concepts in Fine-Tuning of Large Language Models (LLMs)

Marktechpost

JANUARY 28, 2025

Despite challenges such as data scarcity and computational demands, innovations like zero-shot learning and iterative optimization continue to push the boundaries of LLM capabilities. Individuals, AI researchers, etc.,

Large Language Models

Large Language Models LLM Data Scarcity Explainability

This AI Paper Introduces SRDF: A Self-Refining Data Flywheel for High-Quality Vision-and-Language Navigation Datasets

Marktechpost

DECEMBER 15, 2024

The researchers also reported enhanced instruction diversity and richness, with over 10,000 unique words incorporated into the SRDF-generated dataset, addressing the vocabulary limitations of previous datasets. The SRDF approach addresses the long-standing challenge of data scarcity in VLN by automating dataset refinement.

Data Scarcity

Data Scarcity Data Quality Automation AI

Splunk Researchers Introduce MAG-V: A Multi-Agent Framework For Synthetic Data Generation and Reliable AI Trajectory Verification

Marktechpost

DECEMBER 10, 2024

By generating synthetic datasets, MAG-V reduces dependence on real customer data, addressing privacy concerns and data scarcity. The frameworks ability to verify trajectories using statistical and embedding-based features represents progress in AI system reliability. Dont Forget to join our 60k+ ML SubReddit.

Machine Learning

Machine Learning Data Scarcity LLM Large Language Models

Innovations in AI: How Small Language Models are Shaping the Future

Pickl AI

OCTOBER 9, 2024

These benefits position SLMs as an attractive option for businesses looking to integrate AI into their operations effectively and responsibly. Data Scarcity Although they perform well with limited data, the effectiveness of SLMs can diminish if they are not adequately trained on relevant datasets.

Natural Language Processing

Natural Language Processing Data Scarcity Large Language Models AI

Meet Meta’s Speech-to-Text, Text-to-Speech model for more than 1100+ languages

Mlearning.ai

MAY 23, 2023

This innovative approach tackles the data scarcity issue for less common languages, allowing MMS to surpass this limitation. Most of us have used a AI assisant on the phone. This dependency significantly restricts the quantity of available training data, as manually generating transcriptions is both expensive and laborious.

Data Scarcity

Data Scarcity Algorithm OpenAI Machine Learning

Synthetic Data: A Model Training Solution

Viso.ai

DECEMBER 18, 2023

Instead of relying on organic events, we generate this data through computer simulations or generative models. Synthetic data can augment existing datasets, create new datasets, or simulate unique scenarios. Specifically, it solves two key problems: data scarcity and privacy concerns.

Computer Vision

Computer Vision Neural Network Auto-complete Data Scarcity

Best practices to build generative AI applications on AWS

AWS Machine Learning Blog

MARCH 14, 2024

More and more customers are building their own FMs using SageMaker, including Stability AI, AI21 Labs, Hugging Face, Perplexity AI, Hippocratic AI, LG AI Research, and Technology Innovation Institute. Dealing with limited target data – In some cases, there is limited real-world data available for the target task.

Generative AI

Generative AI Prompt Engineering Prompt Engineer AI

The Rise of Domain-Specific Language Models

Unite.AI

MARCH 13, 2024

Data Availability and Quality : Obtaining high-quality, domain-specific datasets is crucial for training accurate and reliable DSLMs. Issues such as data scarcity, bias, and noise can significantly impact model performance.

Natural Language Processing

Natural Language Processing Large Language Models Data Scarcity LLM

This AI Paper Explores How Formal Systems Could Revolutionize Math LLMs

Marktechpost

DECEMBER 28, 2024

Many AI models excel in solving high school-level mathematical problems but struggle with advanced tasks such as theorem proving and abstract logical deductions. These challenges are compounded by data scarcity in advanced mathematics and the inherent difficulty of verifying intricate logical reasoning.

Data Scarcity

Data Scarcity Natural Language Processing Artificial Intelligence Artificial Intelligence

Open Artificial Knowledge (OAK) Dataset: A Large-Scale Resource for AI Research Derived from Wikipedia’s Main Categories

NeoBERT: Modernizing Encoder Models for Enhanced Language Understanding

Webinars

Trending Sources

AI Researchers At Mayo Clinic Introduce A Machine Learning-Based Method For Leveraging Diffusion Models To Construct A Multitask Brain Tumor Inpainting Algorithm

Webinars

Meta AI Researchers Introduce Token-Level Detective Reward Model (TLDR) to Provide Fine-Grained Annotations for Large Vision Language Models

Amazon AI Research Introduces BioBRIDGE: A Parameter-Efficient Machine Learning Framework to Bridge Independently Trained Unimodal Foundation Models to Establish Multimodal Behavior

Full Guide on LLM Synthetic Data Generation

A New AI Research from China Proposes SHIP: A Plug-and-Play Generative AI Approach to Improve Existing Fine-Tuning Methods

Meet LP-MusicCaps: A Tag-to-Pseudo Caption Generation Approach with Large Language Models to Address the Data Scarcity Issue in Automatic Music Captioning

This Paper Introduces TF-T2V: A Novel Text-to-Video Generation Framework with Impressive Scalability and Performance Improvements

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

This Paper Explores AI-Driven Hedging Strategies in Finance: A Deep Dive into the Use of Recurrent Neural Networks and k-Armed Bandit Models for Efficient Market Simulation and Risk Management

University of Cambridge Researchers Introduce a Dataset of 50,000 Synthetic and Photorealistic Foot Images along with a Novel AI Library for Foot

Data-Centric AI: The Importance of Systematically Engineering Training Data

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

ByteDance Researchers Introduce Tarsier2: A Large Vision-Language Model (LVLM) with 7B Parameters, Designed to Address the Core Challenges of Video Understanding

Few-Shot Preference Optimization (FSPO): A Novel Machine Learning Framework Designed to Model Diverse Sub-Populations in Preference Datasets to Elicit Personalization in Language Models for Open-Ended Question Answering

A Comprehensive Guide to Concepts in Fine-Tuning of Large Language Models (LLMs)

This AI Paper Introduces SRDF: A Self-Refining Data Flywheel for High-Quality Vision-and-Language Navigation Datasets

Splunk Researchers Introduce MAG-V: A Multi-Agent Framework For Synthetic Data Generation and Reliable AI Trajectory Verification

Innovations in AI: How Small Language Models are Shaping the Future

Meet Meta’s Speech-to-Text, Text-to-Speech model for more than 1100+ languages

Synthetic Data: A Model Training Solution

Best practices to build generative AI applications on AWS

The Rise of Domain-Specific Language Models

This AI Paper Explores How Formal Systems Could Revolutionize Math LLMs

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