​[[{“value”:” Microsoft addresses the complex challenges of integrating geospatial data into machine learning workflows. Working with such data is difficult due to its heterogeneity, coming in multiple formats and varying resolutions, and its complexity, involving features like occlusions, scale variations, and atmospheric interference. Additionally, geospatial… Read More »TorchGeo 0.6.0 Released by Microsoft: Helping Machine Learning Experts to Work with Geospatial Data Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Adapting 2D-based segmentation models to effectively process and segment 3D data presents a significant challenge in the field of computer vision. Traditional approaches often struggle to preserve the inherent spatial relationships in 3D data, leading to inaccuracies in segmentation. This challenge is critical for… Read More »SAM2Point: A Preliminary Exploration Adapting Segment Anything Model 2 (SAM 2) for Zero-Shot and Promptable 3D Segmentation Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Social network generation finds numerous applications in various fields, such as epidemic modeling, social media simulations, and understanding social phenomena like polarization. Creating realistic social networks is crucial when real networks cannot be directly observed due to privacy concerns or other constraints. These generated… Read More »Stanford Researchers Examine LLM Social Network Generation and Bias in Political Homophily Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have significantly progressed in various domains, including natural language understanding and code generation. These models can generate coherent text and solve complex tasks. However, LLMs face challenges when applied to more specialized areas such as competitive programming and code generation.… Read More »Scale AI Proposes PlanSearch: A New SOTA Test-Time Compute Method to Enhance Diversity and Efficiency in Large Language Model Code Generation Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Graph neural networks (GNNs) have emerged as powerful tools for capturing complex interactions in real-world entities and finding applications across various business domains. These networks excel at generating effective graph entity embeddings by encoding both node features and structural insights, making them invaluable for… Read More »OpenFGL: A Comprehensive Benchmark for Advancing Federated Graph Learning Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Artificial intelligence (AI) and database management systems have increasingly converged, with significant potential to improve how users interact with large datasets. Recent advancements aim to allow users to pose natural language questions directly to databases and retrieve detailed, complex answers. However, current tools are… Read More »Table-Augmented Generation (TAG): A Breakthrough Model Achieving Up to 65% Accuracy and 3.1x Faster Query Execution for Complex Natural Language Queries Over Databases, Outperforming Text2SQL and RAG Methods Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Mixture-of-experts (MoE) architectures are becoming significant in the rapidly developing field of Artificial Intelligence (AI), allowing for the creation of systems that are more effective, scalable, and adaptable. MoE optimizes computing power and resource utilization by employing a system of specialized sub-models, or experts,… Read More »Mixture-of-Experts (MoE) Architectures: Transforming Artificial Intelligence AI with Open-Source Frameworks Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have become fundamental tools for tasks such as question-answering (QA) and text summarization. These models excel at processing long and complex texts, with capacities reaching over 100,000 tokens. As LLMs are popular for handling large-context tasks, ensuring their reliability and… Read More »LongBench-Cite and LongCite-45k: Leveraging CoF (Coarse to Fine) Pipeline to Enhance Long-Context LLMs with Fine-Grained Sentence-Level Citations for Improved QA Accuracy and Trustworthiness Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Graph Neural Networks (GNNs) have emerged as the leading approach for graph learning tasks across various domains, including recommender systems, social networks, and bioinformatics. However, GNNs have shown vulnerability to adversarial attacks, particularly structural attacks that modify graph edges. These attacks pose significant challenges… Read More »SFR-GNN: A Novel Graph Neural Networks (GNN) Model that Employs an ‘Attribute Pre-Training and Structure Fine-Tuning’ Strategy to Achieve Robustness Against Structural Attacks Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The paper “MemLong: Memory-Augmented Retrieval for Long Text Modeling” addresses a critical limitation regarding the ability to process long contexts in the field of Large Language Models (LLMs). While LLMs have shown remarkable success in various applications, they struggle with long-sequence tasks due to… Read More »MemLong: Revolutionizing Long-Context Language Modeling with Memory-Augmented Retrieval Shreya Maji Artificial Intelligence Category – MarkTechPost