Moreover, we discuss strategies for metadata selection and human evaluation to ensure the quality and effectiveness of ITDs. By integrating these elements, this tutorial provides a structured ...
Abstract: Most recommender systems have been proposed by utilizing the user feedback data, where implicit feedback is often used. However, in this setting, the dispreference signals in the original ...
Digital engineering and modeling and simulation (M&S) are transformative approaches that enable precision, efficiency and innovation in munitions production and warfighter capabilities. By integrating ...
Abstract: In this paper, we propose “SoundSpring”, a cutting-edge error-resilient audio transceiver that marries the robustness benefits of joint source-channel coding (JSCC) while also being ...
Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.
REC-R1 is a general framework that bridges generative large language models (LLMs) and recommendation systems via reinforcement learning. Check the paper here.
A hands-on tutorial series for building LangGraph agents with local LLMs via Ollama. Each notebook teaches a concept from scratch - no cloud APIs required.
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