​[[{“value”:” Governments and humanitarian organizations need reliable data on building and infrastructure changes over time to manage urbanization, allocate resources, and respond to crises. However, many regions across the Global South need more access to timely and accurate data on buildings, making it difficult to… Read More »Google AI Introduces the Open Buildings 2.5D Temporal Dataset that Tracks Building Changes Across the Global South Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Integer Linear Programming (ILP) is the foundation of combinatorial optimization, which is extensively applied across numerous industries to resolve challenging decision-making issues. Under a set of linear equality constraints, an ILP aims to minimize or maximize a linear objective function, with the important condition… Read More »This Research Paper Discusses Space-Efficient Algorithms for Integer Programming with Few Constraints Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Input space mode connectivity in deep neural networks builds upon research on excessive input invariance, blind spots, and connectivity between inputs yielding similar outputs. The phenomenon exists generally, even in untrained networks, as evidenced by empirical and theoretical findings. This research expands the scope… Read More »Exploring Input Space Mode Connectivity: Insights into Adversarial Detection and Deep Neural Network Interpretability Shoaib Nazir Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Multi-agent reinforcement learning (MARL) is a field focused on developing systems where multiple agents cooperate to solve tasks that exceed the capabilities of individual agents. This area has garnered significant attention due to its relevance in autonomous vehicles, robotics, and complex gaming environments. The… Read More »HARP (Human-Assisted Regrouping with Permutation Invariant Critic): A Multi-Agent Reinforcement Learning Framework for Improving Dynamic Grouping and Performance with Minimal Human Intervention Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” This post dives into the application of tree-based models, particularly focusing on decision trees, bagging, and random forests within the Ames Housing dataset. It begins by emphasizing the critical role of preprocessing, a fundamental step that ensures our data is optimally configured for the… Read More »From Single Trees to Forests: Enhancing Real Estate Predictions with Ensembles Vinod Chugani MachineLearningMastery.com

​[[{“value”:” Artificial Intelligence (AI) safety has become an increasingly crucial area of research, particularly as large language models (LLMs) are employed in various applications. These models, designed to perform complex tasks such as solving symbolic mathematics problems, must be safeguarded against generating harmful or unethical… Read More »MathPrompt: A Novel AI Method for Evading AI Safety Mechanisms through Mathematical Encoding Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In artificial intelligence and natural language processing, long-context reasoning has emerged as a crucial area of research. As the volume of information that needs to be processed grows, machines must be able to synthesize and extract relevant data from massive datasets efficiently. This goes… Read More »Michelangelo: An Artificial Intelligence Framework for Evaluating Long-Context Reasoning in Large Language Models Beyond Simple Retrieval Tasks Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Computational reproducibility poses a significant challenge in scientific research across various fields, including psychology, economics, medicine, and computer science. Despite the fundamental importance of reproducing results using provided data and code, recent studies have exposed severe shortcomings in this area. Researchers face numerous obstacles… Read More »CORE-Bench: A Benchmark Consisting of 270 Tasks based on 90 Scientific Papers Across Computer Science, Social Science, and Medicine with Python or R Codebases Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Federated Learning (FL) is a technique that allows Machine Learning models to be trained on decentralized data sources while preserving privacy. This method is especially helpful in industries like healthcare and finance, where privacy issues prevent data from being centralized. However, there are big… Read More »HERL (Homomorphic Encryption Reinforcement Learning): A Reinforcement Learning-based Approach that Uses Q-Learning to Dynamically Optimize Encryption Parameters Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Chain-of-thought (CoT) prompting has emerged as a popular technique to enhance large language models’ (LLMs) problem-solving abilities by generating intermediate steps. Despite its better performance in mathematical reasoning, CoT’s effectiveness in other domains remains questionable. Current research is focused more on mathematical problems, possibly… Read More »Chain-of-Thought (CoT) Prompting: A Comprehensive Analysis Reveals Limited Effectiveness Beyond Math and Symbolic Reasoning Sajjad Ansari Artificial Intelligence Category – MarkTechPost