arXiv:2601.00243v1 Announce Type: new Abstract: Effective pest management is crucial for enhancing agricultural productivity, especially for crops such as sugarcane and wheat that are highly vulnerable to pest infestations. Traditional pest management methods depend heavily on manual field inspections and the use of chemical pesticides. These approaches are often costly, time-consuming, labor-intensive, and can have a negative impact on the environment. To overcome these challenges, this study presents a lightweight framework for pest detection and pesticide recommendation, designed […]

Ver mais

We study the problem of online multi-class learning with partial feedback: in each trial of online learning, instead of providing the true class label for a given instance, the oracle will only reveal to the learner if the predicted class label is correct. We present a general framework for online multi-class learning with partial feedback that adapts the potential-based gradient descent approaches (Cesa-Bianchi & Lugosi, 2006). The generality of the proposed framework is verified by the fact that […]

Ver mais

Human-guided AI collaboration The post Probabilistic Multi-Variant Reasoning: Turning Fluent LLM Answers Into Weighted Options appeared first on Towards Data Science.

Ver mais

MCP is a key enabler into turning your LLM into an agent by providing it with tools to retrieve real-time information or perform actions. In this deep dive we cover how MCP works, when to use it, and what to watch out for. The post Tools for Your LLM: a Deep Dive into MCP appeared first on Towards Data Science.

Ver mais

arXiv:2601.02387v1 Announce Type: new Abstract: Satellite networks with wide coverage are considered natural extensions to terrestrial networks for their long-distance end-to-end (E2E) service provisioning. However, the inherent topology dynamics of low earth orbit satellite networks and the uncertain network scales bring an inevitable requirement that resource chains for E2E service provisioning must be efficiently re-planned. Therefore, achieving highly adaptive resource management is of great significance in practical deployment applications. This paper first designs a regional resource management (RRM) […]

Ver mais

Deep learning, despite its remarkable successes, is a young field – perhaps ten years old. While models called artificial neural networks have been studied for decades, much of that work seems only tenuously connected to modern results. It’s often the case that young fields start in a very ad-hoc manner. Later, the mature field is understood very differently than it was understood by its early practitioners. It seems quite likely that deep learning is in this ad-hoc state… […]

Ver mais

Our top reads on AI workslop, visualizing strategy, Taylor Swift, and more.

Ver mais