Research Progress on the Localized Application of the Objective Structured Clinical Examination in Higher Vocational Nursing ...

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...

Abstract: Multi-objective reinforcement learning (MORL) is a structured approach for optimizing tasks with multiple objectives. However, it often relies on pre-defined reward functions, which can be ...

RLP uses a single network (shared parameters) to (1) sample a CoT policy 𝜋 𝜃 ( 𝑐 𝑡 ∣ 𝑥 < 𝑡 ) π θ (c t ∣x <t ) and then (2) score the next token 𝑝 𝜃 ( 𝑥 𝑡 ∣ 𝑥 < 𝑡 , 𝑐 𝑡 ) p θ (x t ∣x <t ...

What are the differences between lesson objectives, learning objectives and success criteria and how can we sharpen our lesson planning and pedagogical choices? Helen Webb offers some practical ...

Rick: A lot of parents and educators may be familiar with the phrase “mastery learning” but not have a clear idea what it means in practice. What is it exactly? Scott: My journey began in 2012 when I ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

1 Research Institute of Petroleum Exploration and Development, PetroChina, Beijing, China 2 Faculty of Petroleum, China University of Petroleum-Beijing at Karamay, Karamay, China Lithology ...

To be useful, the assessments you give students must meet two conditions. First, assessments must be appropriately challenging at the moment when they are given. A question that’s clearly too hard or ...