Marktechpost

APRIL 5, 2024

State-of-the-art language models require vast amounts of text data for pretraining, often in the order of trillions of words, which poses a challenge for smaller languages needing more extensive resources.

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Marktechpost

MAY 11, 2024

The emergence of large language models (LLMs) has renewed interest in hierarchical control architectures, with recent studies utilizing LLMs to replace symbolic planners, achieving significant feats like mobile object rearrangement based on open-vocabulary instructions.

Large Language Models 110

Large Language Models Robotics Neural Network LLM 110

Marktechpost

FEBRUARY 25, 2024

Much like how foundation models in language, such as BERT and GPT, have transformed natural language processing by leveraging vast textual data, pretrained foundation models hold similar promise for SDM. All credit for this research goes to the researchers of this project.

Machine Learning 125

Machine Learning Natural Language Processing Robotics BERT 125

Marktechpost

FEBRUARY 20, 2024

Studying scaling laws in large language models (LLMs) is crucial for enhancing machine translation performance. Of all the major challenges associated with the field, a key challenge in advancing LLMs is determining the effect of pretraining data size and its alignment with downstream tasks, particularly in machine translation.

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Unite.AI

OCTOBER 27, 2023

Scaling up representations of text and visuals has been a major focus of research in recent years. Developments and research conducted in the recent past have led to numerous revolutions in language learning and vision. Today, we will discuss Uni3D, a 3D foundation model that aims to explore unified 3D representations.

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Marktechpost

MARCH 18, 2024

In a new AI research paper , Google researchers introduced a pre-trained scorer model, Cappy , to enhance and surpass the performance of large multi-task language models. The paper aims to resolve challenges faced in the large language models (LLMs). Check out the Paper. Check out the Paper.

Machine Learning 119

Machine Learning Natural Language Processing Large Language Models LLM 119

Marktechpost

JANUARY 6, 2024

Significant achievements have been made in LLMs, exemplified by ChatGPT, excelling in complex language processing tasks. This limits the performance of LLMs in other non-English languages, which is a matter of concern for non-English users. While many LLMs comprehend diverse languages, imbalanced language resources pose challenges.

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LLM ChatGPT ML Large Language Models 124

Marktechpost

MAY 15, 2024

Salesforce AI Research has unveiled a groundbreaking development – the XGen-MM series. The Genesis of XGen-MM: XGen-MM emerges from Salesforce’s unified XGen initiative, reflecting a concerted effort to pioneer large foundation models. Conclusion: In multimodal language models, XGen-MM emerges as a beacon of innovation.

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Marktechpost

OCTOBER 17, 2023

Researchers from Nvidia and the University of Illinois at Urbana Champaign introduce Retro 48B, a significantly larger language model than previous retrieval-augmented models like Retro (7.5B Their approach reduces model perplexity, improves factuality, and enhances task performance post-fine-tuning. parameters).

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LLM Large Language Models AI Researcher AI Research 132

Marktechpost

FEBRUARY 28, 2024

Large language models can accomplish tasks that surpass current paradigms, such as reading code at the repository level, modeling long-history dialogs, and powering autonomous agents with language models with a context window of 128K tokens. The team’s foundational models are LLaMA-2 7B and 13B.

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Marktechpost

DECEMBER 10, 2023

Natural language processing (NLP) has entered a transformational period with the introduction of Large Language Models (LLMs), like the GPT series, setting new performance standards for various linguistic tasks. Autoregressive pretraining has substantially contributed to computer vision in addition to NLP.

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Marktechpost

JANUARY 21, 2024

The inherent capabilities of pretrained large language models are notable, yet achieving desired behaviors often requires additional adaptation. When dealing with models whose weights are kept private, the challenge intensifies, rendering tuning either excessively costly or outright impossible.

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Marktechpost

JANUARY 29, 2024

With new releases and introductions in the field of Artificial Intelligence (AI), Large Language Models (LLMs) are advancing significantly. They are showcasing their incredible capability of generating and comprehending natural language.

Large Language Models 128

Large Language Models Data Scarcity Artificial Intelligence Artificial Intelligence 128

Marktechpost

MARCH 4, 2024

The recent success of large language models relies heavily on extensive text datasets for pre-training. Despite the expanding interest in this area, limited resources hinder extensive research. Despite the expanding interest in this area, limited resources hinder extensive research.

Large Language Models 113

Large Language Models Categorization AI AI 113

Marktechpost

MARCH 1, 2024

The quest for clean, usable data for pretraining Large Language Models (LLMs) resembles searching for treasure amidst chaos. NeuScraper’s architecture begins by dissecting webpages into blocks, analyzing them through the prism of a shallow neural model that understands the webpage’s layout.

Large Language Models 121

Large Language Models Data Extraction Neural Network LLM 121

Marktechpost

MAY 15, 2024

Pre-training large models on time series data faces several challenges: the lack of a comprehensive public time series repository, the complexity of diverse time series characteristics, and the infancy of experimental benchmarks for model evaluation, especially under resource-constrained and minimally supervised scenarios.

Machine Learning 126

Machine Learning Deep Learning ML Artificial Intelligence 126

Marktechpost

JANUARY 10, 2024

BERT is a language model which was released by Google in 2018. It is based on the transformer architecture and is known for its significant improvement over previous state-of-the-art models. In this research paper, the authors have shown that speed optimizations can be incorporated into the BERT architecture and training recipe.

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Marktechpost

JANUARY 24, 2024

These models align global image and text features in a shared space through similar and dissimilar pairs, excelling in tasks like image classification and retrieval. Despite these advancements, challenges like computational expense and reliance on pretrained models persist.

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Marktechpost

SEPTEMBER 3, 2023

Large language models like GPT-3 and their impact on various aspects of society are a subject of significant interest and debate. Large language models have significantly advanced the field of NLP. Similar to large language models in other languages, Arabic LLMs may inherit biases from the training data.

Large Language Models 125

Large Language Models Natural Language Processing NLP Artificial Intelligence 125

Marktechpost

SEPTEMBER 30, 2023

Researchers continually strive to build models that can understand, reason, and generate text like humans in the rapidly evolving field of natural language processing. These models must grapple with complex linguistic nuances, bridge language gaps, and adapt to diverse tasks.

Artificial Intelligence 123

Artificial Intelligence Artificial Intelligence Natural Language Processing NLP 123

Marktechpost

MARCH 14, 2024

Advancements in large language models (LLMs) have been witnessed across various domains, such as translation, healthcare, and code generation. These models have shown exceptional capabilities in understanding and generating human-like text. Despite their success, the legal domain has yet to benefit fully from this technology.

Large Language Models 108

Large Language Models LLM Artificial Intelligence Artificial Intelligence 108

Marktechpost

JANUARY 22, 2024

Many people are now interested in the state space model (SSM) because of how recent research has advanced. Modern SSMs, which derive from the classic state space model, benefit from concurrent training and excel at capturing long-range dependencies. These methods excel at modeling long-range dependencies.

Computer Vision 128

Computer Vision Artificial Intelligence Artificial Intelligence Robotics 128

Marktechpost

SEPTEMBER 26, 2023

Domain-specific big language models have emerged due to the oversaturation of general large language models (LLMs). The first builds models from scratch using a combination of generic and domain-specific corpora. The second method, which is more economical, refines the language model using supervised datasets.

Large Language Models 124

Large Language Models Natural Language Processing LLM AI 124

Marktechpost

JANUARY 18, 2024

With the advancements in Natural Language Processing and Natural Language Generation, Large Language Models (LLMs) are being frequently used in real-world applications. With their ability to mimic human behavior, these models, with their general-purpose nature, have stepped into every field and domain.

Natural Language Processing 95

Natural Language Processing Large Language Models LLM AI 95

Marktechpost

APRIL 10, 2024

Language models often need more exposure to fruitful mistakes during training, hindering their ability to anticipate consequences beyond the next token. Transformer-based models struggle with planning due to error snowballing and difficulty in lookahead tasks. Yet, these methods are limited by the demonstrated procedures.

Machine Learning 138

Machine Learning Algorithm ML Artificial Intelligence 138

Marktechpost

MARCH 7, 2024

Recent advancements in language technology have revolutionized the adaptation of Large Language Models (LLMs), leveraging extensive in-domain datasets or even just a handful of task-specific examples. How can language models be adapted to follow instructions in specialized domains without annotated data?

AI Modeling 95

AI Modeling Large Language Models NLP AI 95

Marktechpost

APRIL 24, 2024

Existing research in Robotic Process Automation (RPA) has focused on rule-based systems like UiPath and Blue Prism, which automate routine tasks such as data entry and customer service. Researchers at J.P. In conclusion, the research introduced FlowMind, developed by J.P. Morgan AI Research. Check out the Paper.

Machine Learning 138

Machine Learning AI Researcher AI Research Large Language Models 138

Marktechpost

NOVEMBER 13, 2023

Researchers from Google DeepMind explore the in-context learning (ICL) capabilities of large language models, specifically transformers, trained on diverse task families. However, their study needs to work on out-of-domain tasks, revealing limitations in generalization for functions beyond the pretraining distribution.

Large Language Models 93

Large Language Models AI AI AI Researcher 93

Marktechpost

MARCH 7, 2024

In the ever-evolving landscape of computational linguistics, bridging language barriers has led to remarkable innovations, particularly in regions characterized by a rich tapestry of languages. Southeast Asia, with its linguistic diversity, presents a unique challenge for language technology. Built upon the robust Qwen 1.5

Computational Linguistics 112

Computational Linguistics Algorithm ML AI 112

Marktechpost

APRIL 10, 2024

For too long, the world of natural language processing has been dominated by models that primarily cater to the English language. However, a groundbreaking new development is set to challenge this status quo and usher in a more inclusive era of language models – the Chinese Tiny LLM (CT-LLM). billion code tokens.

LLM 124

LLM Natural Language Processing NLP ML 124

AI News

APRIL 19, 2024

Meta has introduced Llama 3 , the next generation of its state-of-the-art open source large language model (LLM). The tech giant claims Llama 3 establishes new performance benchmarks, surpassing previous industry-leading models like GPT-3.5 Meta’s 70 billion parameter instruction fine-tuned model outperformed GPT-3.5,

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LLM Large Language Models Big Data Responsible AI 250

Marktechpost

NOVEMBER 19, 2023

Researchers confront a formidable challenge within the expansive domain of materials science—efficiently distilling essential insights from densely packed scientific texts. Current methodologies within this domain often lean on general-purpose language models for information extraction.

LLM 138

LLM AI Researcher AI Research ML 138

Unite.AI

APRIL 4, 2024

However, compared to domains like natural language processing and image recognition , the integration of advanced artificial intelligence (AI) techniques into time series forecasting has been relatively slow. Recently, various foundational models have been developed for time series data.

Data Analysis 226

Data Analysis Natural Language Processing Artificial Intelligence Artificial Intelligence 226

Marktechpost

DECEMBER 24, 2023

In contrast, present multimodal models have not mastered people’s ability to learn new tasks in context, meaning that they can do so with minimal demonstrations or instructions. Generative pretrained language models have recently shown impressive skills in learning from context.

Artificial Intelligence 123

Artificial Intelligence Artificial Intelligence AI AI 123

Marktechpost

MAY 1, 2024

Many applications have used large language models (LLMs). Researchers from FAIR, GenAI, and Reality Labs at Meta, University of Toronto, Carnegie Mellon University, University of Wisconsin-Madison, and Dana-Farber Cancer Institute investigate the possibility of decreasing the layer count for each token through early inference exit.

Large Language Models 122

Large Language Models Auto-complete LLM Deep Learning 122

Marktechpost

JANUARY 26, 2024

Tensoic has recently introduced Kannada Llama ( Kan-LLaMA ) to address the limitations of language models (LLMs), focusing specifically on proprietary characteristics, computational resources, and barriers to broader research community contributions.

Natural Language Processing 93

Natural Language Processing NLP LLM AI 93

Unite.AI

DECEMBER 29, 2023

The Emergence of Small Language Models In the rapidly evolving world of artificial intelligence, the size of a language model has often been synonymous with its capability. Smaller language models, once overshadowed by their larger counterparts, are emerging as potent tools in various AI applications.

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