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Tag

#reinforcement learning

5 articles tagged #reinforcement learning

arxivMay 14bullish

HLS-Seek: QoR-Aware Code Generation for High-Level Synthesis via Proxy Comparative Reward Reinforcement Learning

arXiv:2605.13536v1 Announce Type: cross Abstract: High-Level Synthesis (HLS) compiles algorithmic C/C++ descriptions into hardware, with Quality of Results (QoR) -- latency and resource utilization -- critically governed by pragma configurations and code structure. Existing LLM-based HLS approaches

HLGP2 models#reinforcement learning#high-level synthesis#quality of resultsRead on arxiv →
arxivApr 7bullish

Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving

arXiv:2603.13842v2 Announce Type: replace-cross Abstract: End-to-end autonomous driving is typically built upon imitation learning (IL), yet its performance is constrained by the quality of human demonstrations. To overcome this limitation, recent methods incorporate reinforcement learning (RL) thro

PATRDI3 models#autonomous driving#imitation learning#reinforcement learningRead on arxiv →
arxivApr 7bullish

TSPO: Breaking the Double Homogenization Dilemma in Multi-turn Search Policy Optimization

arXiv:2601.22776v2 Announce Type: replace Abstract: Multi-turn tool-integrated reasoning enables Large Language Models (LLMs) to solve complex tasks through iterative information retrieval. However, current reinforcement learning (RL) frameworks for search-augmented reasoning predominantly rely on s

QWQW2 models#reinforcement learning#large language models#reasoningRead on arxiv →
arxivApr 3

Semantic Interaction Information mediates compositional generalization in latent space

arXiv:2603.27134v2 Announce Type: replace Abstract: Are there still barriers to generalization once all relevant variables are known? We address this question via a framework that casts compositional generalization as a variational inference problem over latent variables with parametric interactions

REECFU4 models · +1#machine learning#generalization#reinforcement learningRead on arxiv →
arxivApr 3bullish

Adaptive Regime-Aware Stock Price Prediction Using Autoencoder-Gated Dual Node Transformers with Reinforcement Learning Control

arXiv:2603.19136v2 Announce Type: replace Abstract: Stock markets exhibit regime-dependent behavior where prediction models optimized for stable conditions often fail during volatile periods. Existing approaches typically treat all market states uniformly or require manual regime labeling, which is

AUDUSO3 models#machine learning#stock market#predictionRead on arxiv →
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