#adaptive learning

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4 papers match

cs.AI2026

Self-Improvements in Modern Agentic Systems: A Survey

Zhe Ren, Yimeng Chen, Dandan Guo +9

The paper surveys modern self-improving autonomous agents, presenting a system-level framework that combines foundation models with prompts, memory, tools, and control logic, and c…

#self-improving agents#autonomous systems#foundation models#adaptive learning
cs.LG2026

SteinGate: Tail-Sensitive Safe Reinforcement Learning via Stein Discrepancy

Yassine Chemingui, Chenhua Fan, Honghao Wei +1

SteinGate introduces a distributional safety certificate based on Kernelized Stein Discrepancy to detect rare, high-cost tail events in reinforcement learning and dynamically switc…

#safe reinforcement learning#tail risk#stein discrepancy#distributional safety
cs.CY2026

Learning in Blocks: A Multi Agent Debate Assisted Personalized Adaptive Learning Framework for Language Learning

Nicy Scaria, Silvester John Joseph Kennedy, Deepak Subramani

The paper presents Learning in Blocks, a framework that uses specialized AI agents to debate and score open‑ended language conversations against CEFR rubrics, then recommends targe…

#language learning#adaptive learning#multi-agent systems#conversation assessment
cs.AI2026

InqEduAgent: Adaptive AI Learning Partners with Gaussian Process Augmentation

Wen-Xi Yang, Tian-Fang Zhao, Guan Liu

The paper presents InqEduAgent, a framework that uses large language models combined with a Gaussian‑process‑based matching mechanism to adaptively select AI learning partners for…

#adaptive learning#inquiry-based education#large language models#gaussian processes