CC-SAM: Achieving Superior Medical Image Segmentation with 85.20 Dice Score and 27.10 Hausdorff Distance Using Convolutional Neural Network CNN and ViT Integration Asif Razzaq Artificial Intelligence Category – MarkTechPost

[[{“value”:” Medical image segmentation plays a role in modern healthcare, focusing on precisely identifying and delineating anatomical structures within medical scans. This process is fundamental for accurate diagnosis, treatment planning, and monitoring of various diseases. Advances in deep learning have improved the accuracy and efficiency… Read More »CC-SAM: Achieving Superior Medical Image Segmentation with 85.20 Dice Score and 27.10 Hausdorff Distance Using Convolutional Neural Network CNN and ViT Integration Asif Razzaq Artificial Intelligence Category – MarkTechPost

LlamaIndex Workflows: An Event-Driven Approach to Orchestrating Complex AI Applications Nikhil Artificial Intelligence Category – MarkTechPost

[[{“value”:” Artificial intelligence (AI) applications have become increasingly complex, often involving multiple interconnected tasks and components. These systems can include elements such as data loaders, language models, vector databases, and external services, all of which must be integrated seamlessly to execute advanced operations. The challenge… Read More »LlamaIndex Workflows: An Event-Driven Approach to Orchestrating Complex AI Applications Nikhil Artificial Intelligence Category – MarkTechPost

[[{“value”:” Protein language models (PLMs) are trained on large protein databases to predict amino acid sequences and generate feature vectors representing proteins. These models have proven useful in various applications, such as predicting protein folding and mutation effects. A key reason for their success is… Read More »Protein Annotation-Improved Representations (PAIR): A Flexible Fine-Tuning Framework that Employs a Text Decoder to Guide the Fine-Tuning Process of the Encoder Sana Hassan Artificial Intelligence Category – MarkTechPost

[[{“value”:”This paper was accepted at the ACL 2024 Large language models (LLMs) are central to modern natural language processing, delivering exceptional performance in various tasks. However, their substantial computational and memory requirements present challenges, especially for devices with limited DRAM capacity. This paper tackles the… Read More »LLM in a Flash: Efficient Large Language Model Inference with Limited Memory Apple Machine Learning Research

Aligning large language models (LLMs) with human expectations without human-annotated preference data is an important problem. In this paper, we propose a method to evaluate the response preference by using the output probabilities of response pairs under contrastive prompt pairs, which could achieve better performance… Read More »Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation Apple Machine Learning Research

[[{“value”:” Kolmogorov-Arnold Networks (KANs) have emerged as a promising alternative to traditional Multi-Layer Perceptrons (MLPs). Inspired by the Kolmogorov-Arnold representation theorem, these networks utilize neurons that perform simple summation operations. However, the current implementation of KANs poses some challenges in practical applications. Currently, researchers are… Read More »The Kolmogorov-Arnold Theorem Revisited: Why Averaging Functions Work Better Sajjad Ansari Artificial Intelligence Category – MarkTechPost

[[{“value”:” Magpie-ultra, a new dataset by the Argilla team for supervised fine-tuning, has been released, featuring 50,000 instruction-response pairs. This synthetically generated dataset utilizes the advanced Llama 3.1 405B-Instruct model and other Llama models like Llama-Guard-3-8B and Meta-Llama-3.1-8B-Instruct. The dataset covers various tasks, including coding,… Read More »Magpie-Ultra Dataset Released: Harnessing Llama 3.1 405B for Diverse AI Instruction-Response Pairs Mohammad Asjad Artificial Intelligence Category – MarkTechPost

[[{“value”:” Large Language Models (LLMs) have transformed artificial intelligence, particularly in developing agent-based systems. These systems require interacting with various environments and executing actions to achieve specific goals. Enhancing the planning capabilities of LLM-based agents has become a critical area of research due to the… Read More »AgentGen: Automating Environment and Task Generation to Enhance Planning Abilities in LLM-Based Agents with 592 Environments and 7,246 Trajectories Asif Razzaq Artificial Intelligence Category – MarkTechPost

[[{“value”:” Meta’s recent release of Llama 3.1 has stirred excitement in the AI community, offering an array of remarkable applications. This groundbreaking model, particularly the 405B variant, stands out for its superior performance and open-source accessibility, outpacing even top-tier closed models. Here are ten wild… Read More »Ten Wild Examples of Llama 3.1 Use Cases Sana Hassan Artificial Intelligence Category – MarkTechPost

[[{“value”:” Representational similarity measures are essential tools in machine learning, used to compare internal representations of neural networks. These measures help researchers understand learning dynamics, model behaviors, and performance by providing insights into how different neural network layers and architectures process information. Quantifying the similarity… Read More »ReSi Benchmark: A Comprehensive Evaluation Framework for Neural Network Representational Similarity Across Diverse Domains and Architectures Nikhil Artificial Intelligence Category – MarkTechPost