Unite.AI

JANUARY 24, 2025

The rapid growth of artificial intelligence (AI) has created an immense demand for data. However, as the availability of real-world data reaches its limits , synthetic data is emerging as a critical resource for AI development.

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Marktechpost

JULY 22, 2024

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) has highlighted the critical need for large, diverse, and high-quality datasets to train and evaluate foundation models. OAK dataset offers a comprehensive resource for AI research, derived from Wikipedia’s main categories.

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AI Researcher AI Research Data Scarcity Prompt Engineer 122

Marktechpost

MARCH 1, 2024

However, the scarcity and limited annotation of 3D data present significant challenges for the development and impact of 3D pretraining. One straightforward solution to address the data scarcity issue is to merge multiple existing 3D datasets and employ the combined data for universal 3D backbone pretraining.

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Data Scarcity Natural Language Processing Deep Learning Artificial Intelligence 109

Marktechpost

JUNE 14, 2024

Together, these techniques mitigate the issues of limited target data, improving the model’s adaptability and accuracy. A recent paper published by a Chinese research team proposes a novel approach to combat data scarcity in classification tasks within target domains. Check out the Paper.

Machine Learning 113

Machine Learning Data Scarcity Deep Learning Automation 113

Marktechpost

JANUARY 29, 2024

With new releases and introductions in the field of Artificial Intelligence (AI), Large Language Models (LLMs) are advancing significantly. Other effective strategies to address data scarcity include vocabulary extension and ongoing pretraining.

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Large Language Models Data Scarcity Artificial Intelligence Artificial Intelligence 132

Marktechpost

MARCH 3, 2025

Data Scarcity: Pre-training on small datasets (e.g., While newer models like GTE and CDE improved fine-tuning strategies for tasks like retrieval, they rely on outdated backbone architectures inherited from BERT. Wikipedia + BookCorpus) restricts knowledge diversity.

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BERT Data Scarcity Natural Language Processing Large Language Models 75

Marktechpost

MAY 11, 2024

With the significant advancement in the fields of Artificial Intelligence (AI) and Natural Language Processing (NLP), Large Language Models (LLMs) like GPT have gained attention for producing fluent text without explicitly built grammar or semantic modules.

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Large Language Models NLP Data Scarcity Computational Linguistics 128

Marktechpost

APRIL 17, 2024

In the rapidly evolving landscape of artificial intelligence (AI), the quest for large, diverse, and high-quality datasets represents a significant hurdle.

Data Scarcity 120

Data Scarcity Artificial Intelligence Artificial Intelligence AI Modeling 120

Marktechpost

MARCH 5, 2024

However, judgmental forecasting has introduced a nuanced approach, leveraging human intuition, domain knowledge, and diverse information sources to predict future events under data scarcity and uncertainty. The challenge in predictive forecasting lies in its inherent complexity and the limitations of existing methodologies.

Machine Learning 133

Machine Learning Data Scarcity Automation ML 133

Marktechpost

AUGUST 2, 2024

A major issue in RL is the data scarcity in embodied AI, where agents must interact with physical environments. This problem is exacerbated by the need for substantial reward-labeled data to train agents effectively.

Machine Learning 130

Machine Learning Data Scarcity Large Language Models Robotics 130

Marktechpost

DECEMBER 30, 2023

A fascinating field of study in artificial intelligence and computer vision is the creation of videos based on written descriptions. 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.

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Marktechpost

OCTOBER 11, 2024

In the rapidly evolving landscape of artificial intelligence, the quality and quantity of data play a pivotal role in determining the success of machine learning models. While real-world data provides a rich foundation for training, it often faces limitations such as scarcity, bias, and privacy concerns.

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Data Scarcity Neural Network Natural Language Processing Machine Learning 109

Flipboard

FEBRUARY 14, 2023

Where would you look for a 2023 state of AI infrastructure analysis, if you really needed one? The answer should be obvious, of course, it’s Tel Aviv …

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Data Scarcity AI AI Artificial Intelligence 54

Marktechpost

APRIL 15, 2024

However, these approaches face significant hurdles, including the curse of multilinguality, data scarcity, and the substantial computational resources required. In summary, the SambaLingo methodology represents a significant stride towards democratizing artificial intelligence across linguistic diversity.

Machine Learning 135

Machine Learning Data Scarcity Large Language Models Natural Language Processing 135

Marktechpost

DECEMBER 31, 2023

Artificial intelligence is used in all spheres of life, providing utility in all fields. He highlighted the necessity for effective data use by stressing the significant amount of data many AI systems consume. However, due to high transaction costs and other limitations, continuous trading may not be feasible.

Neural Network 120

Neural Network Data Scarcity Artificial Intelligence Artificial Intelligence 120

Marktechpost

OCTOBER 22, 2024

The dataset was designed to address the major challenges of multilingual multimodal learning: data scarcity, cultural nuances, catastrophic forgetting, and evaluation complexity. Moreover, PANGEA matches or even outperforms proprietary models like Gemini-1.5-Pro

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Large Language Models Data Scarcity Inference Engine LLM 108

Marktechpost

MAY 8, 2024

Over the past decade, advancements in deep learning and artificial intelligence have driven significant strides in self-driving vehicle technology. These technologies have revolutionized computer vision, robotics, and natural language processing and played a pivotal role in the autonomous driving revolution.

Deep Learning 122

Deep Learning Neural Network Data Scarcity Natural Language Processing 122

Marktechpost

JULY 23, 2023

A current PubMed search using the Mesh keywords “artificial intelligence” and “radiology” yielded 5,369 papers in 2021, more than five times the results found in 2011. Data scarcity and data imbalance are two of these challenges.

Machine Learning 98

Machine Learning Data Scarcity Algorithm AI Researcher 98

Marktechpost

APRIL 23, 2024

Integrating artificial intelligence (AI) in healthcare transforms medical practices by improving diagnostics and treatment planning accuracy and efficiency. Unlike conventional methods, this approach utilizes Bayesian inference and Monte Carlo techniques to effectively manage uncertainty and data scarcity.

Deep Learning 102

Deep Learning Data Scarcity Artificial Intelligence Artificial Intelligence 102

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.

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Data Quality Data Scarcity AI AI 157

Marktechpost

AUGUST 3, 2023

The post Meet LP-MusicCaps: A Tag-to-Pseudo Caption Generation Approach with Large Language Models to Address the Data Scarcity Issue in Automatic Music Captioning appeared first on MarkTechPost.

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Data Scarcity Large Language Models BERT Natural Language Processing 52

Marktechpost

APRIL 27, 2024

A few-shot evaluation further confirms FLORA’s proficiency in managing data scarcity and distribution variability, showcasing its robust performance even with limited training examples. In conclusion, FLORA presents a promising solution to the challenge of training vision-language models in federated learning settings.

Machine Learning 133

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Marktechpost

MARCH 26, 2024

In conclusion, the LLM2LLM framework offers a robust solution to the critical challenge of data scarcity. By harnessing the power of one LLM to improve another, it demonstrates a novel, efficient pathway to fine-tune models for specific tasks with limited initial data. Similarly, on the CaseHOLD dataset, there was a 32.6%

Large Language Models 132

Large Language Models Data Scarcity Natural Language Processing LLM 132

Marktechpost

JANUARY 15, 2024

Developed by researchers from Apple, aiming to enhance machine translation, AlignInstruct represents a paradigm shift in tackling data scarcity. This is where the novel concept of contrastive alignment instructions, or AlignInstruct, comes into play.

Large Language Models 130

Large Language Models Data Scarcity Computational Linguistics Natural Language Processing 130

Marktechpost

JULY 8, 2024

In conclusion, the research conducted by Cohere For AI demonstrates the critical importance of high-quality, diverse, multilingual data in training effective multilingual language models.

Data Scarcity 131

Data Scarcity Large Language Models Natural Language Processing NLP 131

NYU Center for Data Science

FEBRUARY 22, 2024

AlphaGeometry not only solved 25 out of 30 recent IMO problems but also presented its solutions in human-readable proofs, marking a significant milestone in the field of artificial intelligence. Reflecting on the broader implications of his work, Trinh articulates an optimistic outlook. By Stephen Thomas

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Marktechpost

APRIL 5, 2024

However, there’s potential to significantly improve models for smaller languages through multilingual training, which could mitigate the data scarcity issue.

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Data Scarcity AI Modeling AI AI 132

Marktechpost

SEPTEMBER 30, 2024

Human-sensing applications such as activity recognition, fall detection, and health monitoring have been revolutionized by advancements in artificial intelligence (AI) and machine learning technologies.

AI Modeling 102

AI Modeling Data Scarcity Artificial Intelligence Artificial Intelligence 102

Marktechpost

AUGUST 12, 2024

The success of VulScribeR highlights the importance of large-scale data augmentation in the field of vulnerability detection. By generating diverse and realistic vulnerable code samples, this approach provides a practical solution to the data scarcity problem that has long hindered the development of effective DLVD models.

Large Language Models 109

Large Language Models Data Scarcity Software Engineer LLM 109

Marktechpost

OCTOBER 15, 2024

These models are trained on data collected from social media, which introduces bias and may not accurately represent diverse patient experiences. Moreover, privacy concerns and data scarcity hinder the development of robust models for mental health diagnosis and treatment.

Data Scarcity 109

Data Scarcity Inference Engine Large Language Models Machine Learning 109

Marktechpost

JULY 18, 2024

In conclusion, YouTube-SL-25 is a pivotal advancement in sign language research, addressing the longstanding data scarcity issue. The dataset’s open-domain nature allows for broad applications, from general sign language pretraining to medium-quality finetuning for specific tasks such as translation and caption alignment.

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Data Scarcity Machine Learning ML Large Language Models 120

Unite.AI

JANUARY 22, 2024

However, generating synthetic data for NLP is non-trivial, demanding high linguistic knowledge, creativity, and diversity. Different methods, such as rule-based and data-driven approaches, have been proposed to generate synthetic data.

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NLP BERT Data Scarcity Large Language Models 167

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. Despite relying just on silhouettes, which are devoid of geometric information, they use surface normals and key points as supplementary clues.

Data Scarcity 127

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Marktechpost

AUGUST 2, 2024

With its extensive language training and romanization technique, the MMS Zero-shot method offers a promising solution to the data scarcity challenge, advancing the field towards more inclusive and universal speech recognition systems.

Data Scarcity 109

Data Scarcity AI Modeling AI AI 109

Marktechpost

MARCH 16, 2024

This method leverages pre-trained generative text and image models to create synthetic paired data for VLMs, addressing data scarcity, cost, and noise challenges. It generates both text and images synthetically, avoiding reliance on real-world data. The researchers from Google DeepMind have proposed Synth2.

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Data Scarcity Computer Vision ML Artificial Intelligence 104

Marktechpost

SEPTEMBER 2, 2023

They optimize the LVLM using synthesized anomalous visual-textual data and incorporating IAD expertise. Direct training using IAD data, however, needs to be improved. Data scarcity is the first. With just a few normal samples, AnomalyGPT can also learn in context, allowing for quick adjustment to new objects.

Data Scarcity 123

Data Scarcity Large Language Models Natural Language Processing LLM 123

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 103

Machine Learning AI Researcher AI Research Data Scarcity 103