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reinforcement learning

2,609 papers

ConnectionMind: Leveraging Social Networks and Large Language Models for Personalized Recommendation at Meta

ConnectionMind is presented, a production-ready recommendation framework that tightly integrates the social network structure with large language models (LLMs) to enable scalable, interpretable, and reasoning-aware personalization in Meta.

Haoyu Han, Yuming Liu, Lei Huang et al. · 0 citations
#reinforcement learning Open access Oct 2026

Towards Reflective AI in Digital Learning Platforms by Reinterpreting AI-Supported Language Learning

A conceptual framework for reflective AI is developed by reinterpreting four existing functions by reinterpreting four existing functions (conversational feedback, pronunciation assessment, adaptive personalization, and gamification) through Schön’s reflection-in-action and models of metacognitive regulation.

Emre Dinç, Fatih Toy · 0 citations
#reinforcement learning Open access Sep 2026

ANALISIS GAYA KEPEMIMPINAN KEPALA SEKOLAH DALAM MENINGKATKAN KINERJA GURU DI SD NEGERI

Principal leadership plays a strategic role in creating a work environment that supports improvements in teaching quality and teacher instructional performance. In the context of changing demands in education, principals are expected not only to manage schools but also to implement participative and adaptive leadership...

Syafani Mayang Septi, Yeni Nuraeni, Rahmawati Eka Saputri · 0 citations

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Microsoft Research Blog Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

Google DeepMind Blog Nov 3, 2026

Agentic cheminformatics with Google Antigravity

Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.

MIT News · Artificial Intelligence Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

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