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UniBench: A Python Library to Evaluate Vision-Language Models VLMs Robustness Across Diverse Benchmarks

Vision-language models (VLMs) have gained significant attention due to their ability to handle various multimodal tasks. However, the rapid proliferation of benchmarks for evaluating these models has created a complex and fragmented landscape. This situation poses several challenges for researchers. Implementing protocols for numerous benchmarks is time-consuming, and interpreting results across multiple evaluation metrics becomes…

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The Evolution of SQL. Unlocking the power of large language… | by 💡Mike Shakhomirov | Aug, 2024

Unlocking the power of large language models Photo by ZHENYU LUO on UnsplashIn this article, I will examine how large language models (LLMs) can convert natural language into SQL, making query writing more accessible to non-technical users. The discussion will include practical examples that showcase the ease of developing LLM-based solutions. We’ll also cover various…

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Retrieval-Augmented Generation Workflows

Introduction Retrieval Augmented Generation, or RAG, is a mechanism that helps large language models (LLMs) like GPT become more useful and knowledgeable by pulling in information from a store of useful data, much like fetching a book from a library. Here’s how retrieval augmented generation makes magic with simple AI workflows: Knowledge Base (Input):…

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What is Retrieval-Augmented Generation?

In the AI space, where technological development is happening at a rapid pace, Retrieval Augmented Generation, or RAG, is a game-changer. But what is RAG, and why does it hold such importance in the present AI and natural language processing (NLP) world? Before answering that question, let's briefly talk about Large Language Models (LLMs).…

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Strengthening Cold Chain Compliance Through Real-Time AI Monitoring

Maintaining strict temperature controls is paramount in cold chain logistics. The integrity of perishable goods, including food and pharmaceuticals, hinges on precise temperature management throughout the supply chain. However, traditional monitoring methods often fall short, leaving gaps that can lead to spoilage, financial losses and regulatory noncompliance. This situation is where real-time AI…

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Data-Augmented Contrastive Tuning: A Breakthrough in Object Hallucination Mitigation

A new research addresses a critical issue in Multimodal Large Language Models (MLLMs): the phenomenon of object hallucination. Object hallucination occurs when these models generate descriptions of objects not present in the input data, leading to inaccuracies undermining their reliability and effectiveness. For instance, a model might incorrectly assert the presence of a “tie” in…

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