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Understand new AI research with readable explanations and links to the original papers.
mcp-proto-okn: Natural-language access to open scientific knowledge graphs through the Model Context Protocol The paper introduces mcp-proto-okn, a tool desi...
Enhancing Multi-Agent Communication through Attention Steering with Context Relevance Multi-agent systems powered by Large Language Models (LLMs) are highly...
KairosAgent is a new framework designed to improve time series forecasting by combining the analytical strengths of Large Language Models (LLMs) with the num...
Demystifying Data Organization for Enhanced LLM Training explores how the order in which training data is presented to a Large Language Model (LLM) significa...
Teaching Values to Machines: Simulating Human-Like Behavior in LLMs explores whether Large Language Models (LLMs) can be guided to adopt coherent, human-like...
Persona Conditioning of Brand Recommendations in Retrieval-Augmented Commercial Chat: A Prominence-Stratified Cross-Provider Audit When you ask an AI for a r...
Physics Is All You Need? A Case Study in Physicist-Supervised AI Development of Scientific Software This paper explores the role of AI agents in scientific s...
SchGen is a new artificial intelligence model designed to automate the creation of printed circuit board (PCB) schematics.
The Challenge of Conflicting Personal Memory As AI agents begin to rely on persistent, multi-source memory, they face a significant hurdle: how to handle inf...
CubePart: An Open-Vocabulary Part-Controllable 3D Generator CubePart is a generative framework designed to create 3D objects that are broken down into specif...
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