Tag: Reinforcement Learning
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Reinforcement Learning Made Powerful: 3 Architectural Insights from OpenTinker’s Cloud-Native Agentic Platform
As reinforcement learning increasingly shifts from isolated research experiments to agentic systems embedded in real workflows, infrastructure has become the limiting factor. Training modern AI agents often requires distributed GPUs,…
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Agentic Reinforcement Learning for Improving Knowledge Graph Question Answering Reliability
Large language models struggle with one-shot SPARQL generation for multi-hop knowledge graph questions, but training them as agentic systems with reinforcement learning enables reliable, iterative query refinement using execution feedback.…
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Adversarial Reinforcement Learning for LLM Agent Safety
As large language models evolve from passive assistants into tool-using agents, a new class of risk emerges. These agents can browse the web, read emails, query databases, and take actions…