A Guide to 400+ Categorized Large Language Model(LLM) Datasets
Analytics Vidhya
NOVEMBER 9, 2024
And to top it off, this collection […] The post A Guide to 400+ Categorized Large Language Model(LLM) Datasets appeared first on Analytics Vidhya.
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Analytics Vidhya
NOVEMBER 9, 2024
And to top it off, this collection […] The post A Guide to 400+ Categorized Large Language Model(LLM) Datasets appeared first on Analytics Vidhya.
Marktechpost
SEPTEMBER 27, 2024
Large language models (LLMs) have revolutionized the field of AI with their ability to generate human-like text and perform complex reasoning. When trained on large datasets, these models often miss critical information from specialized domains, leading to hallucinations or inaccurate responses.
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Marktechpost
APRIL 30, 2024
Large Language Models (LLMs) signify a revolutionary leap in numerous application domains, facilitating impressive accomplishments in diverse tasks. With billions of parameters, these models demand extensive computational resources for operation. Yet, their immense size incurs substantial computational expenses.
Unite.AI
FEBRUARY 28, 2024
Large language models (LLMs) like GPT-4, DALL-E have captivated the public imagination and demonstrated immense potential across a variety of applications. Question answering: They can provide informative answers to natural language questions across a wide range of topics.
Marktechpost
AUGUST 31, 2024
Large Language Models (LLMs) have demonstrated remarkable capabilities in various natural language processing tasks. However, they face a significant challenge: hallucinations, where the models generate responses that are not grounded in the source material. 1% across all datasets after filtering.
Unite.AI
JANUARY 11, 2024
They serve as a core building block in many natural language processing (NLP) applications today, including information retrieval, question answering, semantic search and more. vector embedding Recent advances in large language models (LLMs) like GPT-3 have shown impressive capabilities in few-shot learning and natural language generation.
Marktechpost
APRIL 26, 2024
Graph Machine Learning (Graph ML), especially Graph Neural Networks (GNNs), has emerged to effectively model such data, utilizing deep learning’s message-passing mechanism to capture high-order relationships. Provide a thorough investigation of the potential of graph structures to address the limitations of LLMs.
Marktechpost
MARCH 24, 2024
This method’s core is using a large language model (LLM), which, due to its state-of-the-art text comprehension capabilities, can integrate diverse types of data to improve the accuracy of detecting device-directed speech. If you like our work, you will love our newsletter.
Marktechpost
JUNE 15, 2024
Large Language Models (LLMs) have taken over the Artificial Intelligence (AI) community in recent times. In a Reddit post, a user recently brought attention to the startling quantity of over 700,000 large language models on Hugging Face, which sparked an argument about their usefulness and potential.
Marktechpost
MARCH 8, 2025
Their results suggest that current brain alignment benchmarks remain unsaturated, emphasizing opportunities to refine LLMs for improved alignment with human language processing. The analysis follows a functional localization approach, identifying language-selective neural units.
Marktechpost
JULY 2, 2024
Large Language Models (LLMs) have shown impressive performance in a range of tasks in recent years, especially classification tasks. These models demonstrate amazing performance when given gold labels or options that include the right answer. High-performance metrics indicate that classification tasks are easy.
Unite.AI
SEPTEMBER 10, 2024
The ability to accurately interpret complex visual information is a crucial focus of multimodal large language models (MLLMs). The resulting family of MLLMs, Eagle, surpasses other leading open-source models on major MLLM benchmarks. Several recent MLLMs achieve this by utilizing a mixture of vision encoders.
Artificial Corner
JULY 30, 2023
In this world of complex terminologies, someone who wants to explain Large Language Models (LLMs) to some non-tech guy is a difficult task. So that’s why I tried in this article to explain LLM in simple or to say general language. A transformer architecture is typically implemented as a Large language model.
Unite.AI
JANUARY 17, 2024
Due to their exceptional content creation capabilities, Generative Large Language Models are now at the forefront of the AI revolution, with ongoing efforts to enhance their generative abilities. However, despite rapid advancements, these models require substantial computational power and resources. Let's begin.
Marktechpost
JANUARY 5, 2024
While Document AI (DocAI) has made significant strides in areas such as question answering, categorization, and extraction, real-world applications continue to face persistent hurdles related to accuracy, reliability, contextual understanding, and generalization to new domains. If you like our work, you will love our newsletter.
Marktechpost
DECEMBER 8, 2023
INSTRUCTOR is used to categorize OSS-INSTRUCT-generated data based on embedding similarity. Magicoder demonstrates competitive performance with top code models with a modest parameter size of no more than 7 billion. Evaluation employs benchmarks like HumanEval and MBPP, focusing on the pass1 metric.
Marktechpost
APRIL 6, 2024
AutoTRIZ emphasizes controlling the problem-solving process while drawing problem-related knowledge from the pre-trained large-scale corpora used to train the LLM. AutoTRIZ’s detection results were compared with human experts’ analyses from textbooks categorized into complete match, half match, and no match scenarios.
Marktechpost
JANUARY 20, 2024
The Natural Language Generation (NLG) field stands at the intersection of linguistics and artificial intelligence. Recent advancements in Large Language Models (LLMs) have revolutionized NLG, significantly enhancing the ability of systems to generate coherent and contextually relevant text.
Marktechpost
JANUARY 21, 2024
Large Language Models (LLMs) have exhibited remarkable prowess across various natural language processing tasks. However, applying them to Information Retrieval (IR) tasks remains a challenge due to the scarcity of IR-specific concepts in natural language. If you like our work, you will love our newsletter.
Marktechpost
JANUARY 17, 2024
In large language models (LLMs), the challenge of keeping information up-to-date is significant. As knowledge evolves, these models must adapt to include the latest information. An alternative approach, model editing, offers a way to update the knowledge within these models more efficiently.
IBM Journey to AI blog
MARCH 27, 2024
This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?
Marktechpost
MAY 11, 2024
Despite their expansive capacities, traditional large language models (LLMs) often fail to comprehend and execute the nuanced directives required for precise IE. These challenges primarily manifest in closed IE tasks, where a model must adhere to stringent, pre-defined schemas.
Marktechpost
SEPTEMBER 20, 2024
Previous research on reasoning frameworks in large language models (LLMs) has explored various approaches to enhance problem-solving capabilities. The DoT framework enhances reasoning capabilities in large language models by modeling iterative reasoning as a directed acyclic graph within a single LLM.
Marktechpost
AUGUST 15, 2023
Large language models (LLMs) have achieved amazing results in a variety of Natural Language Processing (NLP), Natural Language Understanding (NLU) and Natural Language Generation (NLG) tasks in recent years. Our survey comprehensively documents the MANY types of self-correction strategies.
Marktechpost
JUNE 19, 2024
These models also offer limited control over the specificity and formatting of topics, hindering their practical application in content analysis and other fields requiring clear thematic categorization. Despite their utility, these models often fail to produce high-quality and easily interpretable topics.
Marktechpost
MARCH 10, 2024
Developing and refining Large Language Models (LLMs) has become a focal point of cutting-edge research in the rapidly evolving field of artificial intelligence, particularly in natural language processing. A significant innovation in this domain is creating a specialized tool to refine the dataset compilation process.
Marktechpost
JULY 4, 2023
Computer programs called large language models provide software with novel options for analyzing and creating text. It is not uncommon for large language models to be trained using petabytes or more of text data, making them tens of terabytes in size. rely on Language Models as their foundation.
Marktechpost
JANUARY 11, 2024
In 2023, the field of artificial intelligence witnessed significant advancements, particularly in the field of large language models. We have categorized them to make it easier to cover maximum tools. Mistral 7B : It is a powerful language model, boasting 7.3
Towards AI
MAY 23, 2023
This is where Large Language Model (LLM) can help. Large Language Models can improve customer service operations, making them more efficient, accurate, and personalized. To become such an adept language processor, the LLM underwent extensive training on massive volumes of text data.
Marktechpost
MARCH 19, 2024
Large language models (LLMs) have taken center stage in artificial intelligence, fueling advancements in many applications, from enhancing conversational AI to powering complex analytical tasks. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup. If you like our work, you will love our newsletter.
Marktechpost
OCTOBER 6, 2024
Training Large Language Models (LLMs) that can handle long-context processing is still a difficult task because of data sparsity constraints, implementation complexity, and training efficiency. Let’s collaborate!
Marktechpost
NOVEMBER 5, 2023
The team hope to expand their current set of high-quality annotations soon to include things like contamination annotations compared to widely-used LLM benchmarks, topic modelling and categorization annotations for each document, and any additional annotations that spark interest in the community. We are also on Telegram and WhatsApp.
Marktechpost
SEPTEMBER 25, 2023
Large Language Models (LLMs) have made significant progress in text creation tasks, among other natural language processing tasks. Existing benchmarks frequently use simple objective metrics like word overlap to gauge how well the content produced by the machine is categorizing information.
Marktechpost
MAY 14, 2024
Research in computational linguistics continues to explore how large language models (LLMs) can be adapted to integrate new knowledge without compromising the integrity of existing information. This structured approach provides a clear view of the impact of fine-tuning with both familiar and novel data on model accuracy.
AssemblyAI
SEPTEMBER 29, 2023
It would take weeks to filter and categorize all of the information to identify common issues or patterns. By using Audio Intelligence, LLMs and frameworks, companies can build on top of ASR to create tools that categorize content, increase searchability, aid in podcast or video editing, and intelligently synthesize this information.
Unite.AI
FEBRUARY 25, 2025
For instance, large language models (LLMs) can analyze human interactions and extract crucial insights that enrich customer experience (CX). Moreover, Gen AI enables companies to collect and categorize data based on shared similarities, uncovering missing dependencies.
MARCH 13, 2025
the end result will be a model good enough to govern a robot in the real world. So far we mostly have academic demonstrations rather than the real-world, commercialized products that large language models are today. Disclosure: Vox Media is one of several publishers that has signed partnership agreements with OpenAI.
Unite.AI
JANUARY 19, 2024
Large language models (LLMs) like GPT-4, PaLM, and Llama have unlocked remarkable advances in natural language generation capabilities. Taxonomy of Hallucination Mitigation Techniques Researchers have introduced diverse techniques to combat hallucinations in LLMs, which can be categorized into: 1.
Marktechpost
OCTOBER 5, 2024
Google Researchers combined AR developments in spatial understanding via SLAM with object detection and segmentation integrated with Multimodal Large Language Model (MLLM) XR Object offers an object-centric interaction in contradistinction to the application-centric approach of Google Lens.
Marktechpost
SEPTEMBER 28, 2023
Auditing Large Language Models (LLMs) has become a paramount concern as these models are increasingly integrated into various applications. This functionality empowers auditors to categorize and group tests based on common themes or model behavior patterns. If you like our work, you will love our newsletter.
Marktechpost
JANUARY 9, 2025
An in-depth error analysis categorized issues into computation errors, logical errors, and step omissions. FREE UPCOMING AI WEBINAR (JAN 15, 2025): Boost LLM Accuracy with Synthetic Data and Evaluation Intelligence Join this webinar to gain actionable insights into boosting LLM model performance and accuracy while safeguarding data privacy.
Marktechpost
MAY 3, 2024
This interdisciplinary field incorporates linguistics, computer science, and mathematics, facilitating automatic translation, text categorization, and sentiment analysis. In sequential single interaction, retrievers identify relevant documents, which the language model then uses to predict the output.
AWS Machine Learning Blog
MARCH 13, 2025
This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular.
Unite.AI
MAY 29, 2024
Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text. Unlocking Unstructured Data with LLMs Leveraging large language models (LLMs) for unstructured data extraction is a compelling solution with distinct advantages that address critical challenges.
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