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Language Model

An In-depth Analysis Comparing Notable AI Models: Llama 3.1, GPT-4.0, and Claude 3.5

Artificial intelligence is continually advancing, with the latest improvements being seen in language models such as Llama 3.1, GPT-4o, and Claude 3.5. These models each bring unique capabilities and numerous advancements that reflect the progression of AI technology. Llama 3.1, developed by Meta, is a breakthrough within the open-source AI community. With its impressive feature…

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Revealing the Moral Hazards of Personalizing ChatGPT: The Case of RogueGPT

Generative Artificial Intelligence (GenAI), specifically large language models (LLMs) like ChatGPT, has transformed the world of natural language processing (NLP). By using deep learning architectures and extensive datasets, these models can generate text that is contextually relevant and coherent, which can significantly improve applications in content creation, customer service, and virtual assistance. Moreover, developments in…

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This AI Article Presents AssistantBench and SeePlanAct: Standard and Agent for Sophisticated Web-Related Tasks

Artificial intelligence (AI) developing systems often encounter several challenges like performing tasks that require human intellect, such as managing complex tasks and interacting with dynamic environments. This necessitates finding and synthesizing information from the web accurately and reliably. Current models face this difficulty, hence pointing out the need for more advanced AI systems. Existing solutions…

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Self-Route: An Easy and Efficient AI Technique that Directs Inquiries to RAG or Long Context LC, drawing on the Model’s Self-Evaluation Capability

Large Language Models (LLMs) like GPT-4 and Gemini-1.5 have revolutionized the field of natural language processing, significantly enhancing text processing applications such as summarization and question answering. However, the long context management required for these applications presents challenges due to computational limitations and cost implications. Recent research has been exploring ways to balance performance and…

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Release Announcement: The Mistral-Large-Instruct-2407, a multilingual AI featuring a 128K context and proficiency in over 80 programming languages, has been launched. With an MMLU (Machine Learning Understanding) score of 84.0% and HumanEval score of 92%, along with solid 93% performance on the GSM8K test, this represents a significant advancement.

AI firm Mistral AI has launched the Mistral Large 2 model, its latest flagship AI model. The new iteration offers significant improvements on its predecessor, with considerable ability in code generation, mathematics, reasoning, and advanced multilingual support. Furthermore, Mistral Large 2 offers enhanced function-calling capabilities and is designed to be cost-efficient, high-speed, and high-performance. Users can…

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Imposter.AI: Revealing Tactics for Adversarial Assaults to Highlight Weaknesses in Sophisticated High Volume Language Models

Large Language Models (LLMs), widely used in automation and content creation, are vulnerable to manipulation by adversarial attacks, leading to significant risk of misinformation, privacy breaches, and enabling criminal activities. According to research led by Meetyou AI Lab, Osaka University and East China Normal University, these sophisticated models are open to harmful exploitation despite safety…

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MIT’s recent AI research indicates that an individual’s perceptions of an LLM significantly influence its efficiency and are critical to its implementation.

MIT and Harvard researchers have highlighted the divergence between human expectations of AI system capabilities and their actual performance, particularly in large language models (LLMs). The inconsistent ability of AI to match human expectations could potentially erode public trust, thereby obstructing the broad adoption of AI technology. This issue, the researchers emphasized, escalates the risk…

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EVAL-LMMS: A Consolidated and Uniform Multimodal AI Evaluation Framework for Clear and Repeatable Assessments

Large Language Models (LLMs) such as GPT-4, Gemini, and Claude have exhibited striking capabilities but evaluating them is complex, necessitating an integrated, transparent, standardized and reproducible framework. Despite the challenges, no comprehensive evaluation technique currently exists, which has hampered progress in this area. However, researchers from the LMMs-Lab Team and S-Lab at NTU, Singapore, developed the…

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Unified and Standardized Multimodal AI Benchmark Framework for Clear and Consistent Evaluations: An LMMS-EVAL Overview

Fundamental large language models (LLMs) including GPT-4, Gemini and Claude have shown significant competencies, matching or surpassing human performance. In this light, benchmarks are necessary tools to determine the strengths and weaknesses of various models. Transparent, standardized and reproducible evaluations are crucial and much needed for language and multimodal models. However, the development of custom…

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