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D-Rax: Improving Radiological Accuracy with Expert-Combined Visual-Language Models

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 9, 202475Views0Likes0Comments
Radiology departments often deal with massive workloads leading to burnout among radiologists. Therefore, tools to help mitigate these issues are essential. VLMs such as LLaVA-Med have advanced significantly in recent years, providing multimodal capabilities for biomedical image and data analysis. However, the generalization and user-friendliness issues of these models have hindered their clinical adoption. To…

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This AI investigation by Tenyx delves into the cognitive abilities of Large Language Models (LLMs) by observing their understanding of geometric principles.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 9, 202461Views0Likes0Comments
Large language models (LLMs) have demonstrated impressive performances across various tasks, with their reasoning capabilities playing a significant role in their development. However, the specific elements driving their improvement are not yet fully understood. Current strategies to enhance reasoning focus on enlarging model size and expanding the context length via methods such as chain of…

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This AI study by Tenyx investigates the logical capabilities of Large Language Models (LLMs) based on their understanding of geometric concepts.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 9, 202473Views0Likes0Comments
Large language models (LLMs) have made remarkable strides in many tasks, with their capacity to reason forming a vital aspect of their development. However, the main drivers behind these advancements remain unclear. Current measures to boost reasoning primarily involve increasing the model's size and extending the context length with methods such as the chain of…

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An Extensive Comparison by Innodata: Evaluating Llama2, Mistral, Gemma, and GPT in terms of Accuracy, Offensive Language, Prejudice, and Tendency to Imagine

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 9, 202462Views0Likes0Comments
A recent study by Innodata assessed various large language models (LLMs), including Llama2, Mistral, Gemma, and GPT for their factuality, toxicity, bias, and hallucination tendencies. The research used fourteen original datasets to evaluate the safety of these models based on their ability to generate factual, unbiased, and appropriate content. Ultimately, the study sought to help…

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Innodata’s Extensive Comparisons of Llama2, Mistral, Gemma and GPT in terms of Accuracy, Harmful Language, Prejudice, and Inclination towards Illusions

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 9, 202469Views0Likes0Comments
An in-depth study by Innodata evaluated the performance of various large language models (LLMs) including Llama2, Mistral, Gemma, and GPT. The study assessed the models based on factuality, toxicity, bias, and propensity for hallucinations and used fourteen unique datasets designed to evaluate each model's safety. One of the main criteria was factuality, the ability of the…

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VCHAR: An Innovative AI Framework that Considers the Results of Simple Tasks as a Distribution Across Defined Ranges

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 9, 202469Views0Likes0Comments
Complex Human Activity Recognition (CHAR) identifies the actions and behaviors of individuals in smart environments, but the process of labeling datasets with precise temporal information of atomic activities (basic human behaviors) is difficult and can lead to errors. Moreover, in real-world scenarios, accurate and detailed labeling is hard to obtain. Addressing this challenge is important…

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The study conducted on Artificial Intelligence by Ohio State University and Carnegie Mellon University delves into the concept of under-the-radar reasoning in Transformers and obtaining generalization via the process of grasping or Grokking.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Tech News, Technology, UncategorizedJuly 9, 202465Views0Likes0Comments
Recent research by scientists at Ohio State University and Carnegie Mellon University has analyzed the limitations of large language models (LLMs), such as GPT-4, and their limitations in implicit reasoning. This refers to their ability to make accurate comparisons of internalized facts and properties, even when aware of the entities in question. The study focused…

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This article proposes Neural Operators as a solution to the generalization challenge by suggesting their use in the modeling of Constitutive Laws.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 9, 202460Views0Likes0Comments
Accurate magnetic hysteresis modeling remains a challenging task that is crucial for optimizing the performance of magnetic devices. Traditional methods, such as recurrent neural networks (RNNs), long short-term memory (LSTM) networks, and gated recurrent units (GRUs), have limitations when it comes to generalizing novel magnetic fields. This generalization is vital for real-world applications. A team of…

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Improving Vision-Language Models: Tackling Multiple-Object Misinterpretation and Incorporating Cultural Diversity for Better Visual Aid in Various Scenarios

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Computer vision, Editors Pick, Staff, Tech News, Technology, UncategorizedJuly 9, 202468Views0Likes0Comments
Vision-Language Models (VLMs) offer immense potential for transforming various applications, including visual assistance for visually impaired individuals. However, their efficacy is often marred by complexities such as multi-object scenarios and diverse cultural contexts. Recent research highlights these issues in two separate studies focused on multi-object hallucination and cultural inclusivity. Hallucination in vision-language models occurs when objects…

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Introducing &AI: An Artificial Intelligence-Based Platform Designed to Simplify Patent Due Diligence Process

AI Startups, Editors Pick, Staff, Tech News, UncategorizedJuly 9, 202474Views0Likes0Comments
Legal firms and patent attorneys are often tasked with assessing the validity of a patent or patent claims for intellectual property litigation or patent applications. They typically hire a third-party search provider to find the necessary evidential materials or conduct keyword research. The process of building a claim chart to assess the claims often takes…

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Introducing DRLQ: A New Approach Utilizing Deep Reinforcement Learning (DRL) for Task Allocation within Quantum Cloud Computing Settings.

AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 9, 202459Views0Likes0Comments
In the rapidly advancing field of quantum computing, managing tasks efficiently and effectively is a complex challenge. Traditional models often struggle due to their heuristic approach, which fails to adapt to the intricacies of quantum computing and can lead to inefficient system performance. Task scheduling, therefore, is critical to minimizing time wastage and optimizing resource…

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