#Reinforcement learning
Latest news articles tagged with "Reinforcement learning". Follow the timeline of events, related topics, and entities.
Articles (6)
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🇺🇸 The Art of Efficient Reasoning: Data, Reward, and Optimization
[USA]
arXiv:2602.20945v1 Announce Type: cross Abstract: Large Language Models (LLMs) consistently benefit from scaled Chain-of-Thought (CoT) reasoning, but also suffer from heavy computational overhead. To...
Related: #AI efficiency, #Computational optimization -
🇺🇸 References Improve LLM Alignment in Non-Verifiable Domains
[USA]
arXiv:2602.16802v1 Announce Type: cross Abstract: While Reinforcement Learning with Verifiable Rewards (RLVR) has shown strong effectiveness in reasoning tasks, it cannot be directly applied to non-v...
Related: #LLM alignment, #Reference‑guided evaluation, #Non‑verifiable domains, #Self‑improvement -
🇺🇸 MedReasoner: Reinforcement Learning Drives Reasoning Grounding from Clinical Thought to Pixel-Level Precision
[USA]
arXiv:2508.08177v3 Announce Type: replace-cross Abstract: Accurately grounding regions of interest (ROIs) is critical for diagnosis and treatment planning in medical imaging. While multimodal large l...
Related: #Medical imaging AI, #Multimodal large language models, #Clinical reasoning grounding, #Pixel‑level precision -
🇺🇸 Decoupling Strategy and Execution in Task-Focused Dialogue via Goal-Oriented Preference Optimization
[USA]
arXiv:2602.15854v1 Announce Type: cross Abstract: Large language models show potential in task-oriented dialogue systems, yet existing training methods often rely on token-level likelihood or prefere...
Related: #Task‑oriented dialogue, #Large language models, #Hierarchical agent design, #Strategy planning -
🇺🇸 FlowSteer: Interactive Agentic Workflow Orchestration via End-to-End Reinforcement Learning
[USA]
arXiv:2602.01664v3 Announce Type: replace Abstract: In recent years, a variety of powerful agentic workflows have been applied to solve a wide range of human problems. However, existing workflow orch...
Related: #Workflow orchestration, #Agentic workflows, #Human‑AI collaboration, #Automation cost reduction -
🇺🇸 Hybrid Reward-Driven Reinforcement Learning for Efficient Quantum Circuit Synthesis
[USA]
arXiv:2507.16641v3 Announce Type: replace-cross Abstract: A reinforcement learning (RL) framework is introduced for the efficient synthesis of quantum circuits that generate specified target quantum ...
Related: #Quantum computing, #Circuit synthesis, #Noisy Intermediate‑Scale Quantum (NISQ), #Fault‑tolerant quantum computing