{"total":32,"rows":[{"id":"2410.04461","title":"Improved Off-policy Reinforcement Learning in Biological Sequence Design","created":"2024-10-06","cited_by_count":13,"area":"deeprl"},{"id":"2505.19850","title":"DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning","created":"2025-05-26","cited_by_count":12,"area":"deeprl"},{"id":"2402.13754","title":"Reinforcement learning-assisted quantum architecture search for variational quantum algorithms","created":"2024-02-21","cited_by_count":10,"area":"deeprl"},{"id":"2603.15789","title":"Emergent Dexterity via Diverse Resets and Large-Scale Reinforcement Learning","created":"2026-03-16","cited_by_count":10,"area":"deeprl"},{"id":"2403.13281","title":"Waypoint-Based Reinforcement Learning for Robot Manipulation Tasks","created":"2024-03-20","cited_by_count":9,"area":"deeprl"},{"id":"2511.20066","title":"SOMBRL: Scalable and Optimistic Model-Based RL","created":"2025-11-25","cited_by_count":7,"area":"deeprl"},{"id":"2402.10228","title":"Q-Star Meets Scalable Posterior Sampling: Bridging Theory and Practice via HyperAgent","created":"2024-02-05","cited_by_count":6,"area":"deeprl"},{"id":"2407.13755","title":"Random Latent Exploration for Deep Reinforcement Learning","created":"2024-07-18","cited_by_count":6,"area":"deeprl"},{"id":"2501.15910","title":"The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective","created":"2025-01-27","cited_by_count":6,"area":"deeprl"},{"id":"2407.00801","title":"Model-Free Active Exploration in Reinforcement Learning","created":"2024-06-30","cited_by_count":5,"area":"deeprl"},{"id":"2601.15353","title":"Reinforcement Learning in the Real World: A Survey of Statistical Challenges and Future Directions","created":"2026-01-21","cited_by_count":5,"area":"deeprl"},{"id":"2407.12185","title":"Satisficing Exploration for Deep Reinforcement Learning","created":"2024-07-16","cited_by_count":4,"area":"deeprl"},{"id":"2503.17678","title":"Computationally and Sample Efficient Safe Reinforcement Learning Using Adaptive Conformal Prediction","created":"2025-03-22","cited_by_count":4,"area":"deeprl"},{"id":"2510.20725","title":"No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes","created":"2025-10-23","cited_by_count":4,"area":"deeprl"},{"id":"2402.17003","title":"Monitoring Fidelity of Online Reinforcement Learning Algorithms in Clinical Trials","created":"2024-02-26","cited_by_count":3,"area":"deeprl"},{"id":"2410.04988","title":"Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling","created":"2024-10-07","cited_by_count":3,"area":"deeprl"},{"id":"2509.18389","title":"Towards Provable Emergence of In-Context Reinforcement Learning","created":"2025-09-22","cited_by_count":3,"area":"deeprl"},{"id":"2406.13127","title":"Oralytics Reinforcement Learning Algorithm","created":"2024-06-19","cited_by_count":2,"area":"deeprl"},{"id":"2412.11743","title":"Generalized Bayesian deep reinforcement learning","created":"2024-12-16","cited_by_count":2,"area":"deeprl"},{"id":"2502.06835","title":"Reinforcement Learning on Dyads to Enhance Medication Adherence","created":"2025-02-06","cited_by_count":2,"area":"deeprl"},{"id":"2410.13490","title":"Novelty-based Sample Reuse for Continuous Robotics Control","created":"2024-10-17","cited_by_count":1,"area":"deeprl"},{"id":"2412.16687","title":"Subgoal Discovery Using a Free Energy Paradigm and State Aggregations","created":"2024-12-21","cited_by_count":1,"area":"deeprl"},{"id":"2509.14077","title":"Online Bayesian Risk-Averse Reinforcement Learning","created":"2025-09-17","cited_by_count":1,"area":"deeprl"},{"id":"2601.03015","title":"In-Context Reinforcement Learning through Bayesian Fusion of Context and Value Prior","created":"2026-01-06","cited_by_count":1,"area":"deeprl"},{"id":"2603.28938","title":"Optimistic Online LQR via Intrinsic Rewards","created":"2026-03-30","cited_by_count":1,"area":"deeprl"},{"id":"2504.04916","title":"Age-of-information minimization under energy harvesting and non-stationary environment","created":"2025-04-07","cited_by_count":0,"area":"deeprl"},{"id":"2507.23084","title":"AutoIndexer: A Reinforcement Learning-Enhanced Index Advisor Towards Scaling Workloads","created":"2025-07-30","cited_by_count":0,"area":"deeprl"},{"id":"2605.09109","title":"When (and How) to Trust the Expert: Diagnosing Query-Time Expert-Guided Reinforcement Learning","created":"2026-05-09","cited_by_count":0,"area":"deeprl"},{"id":"2605.24345","title":"Evolving Robustness--Exploration Trade-off in Online Reinforcement Learning via Quantile Bayesian Risk MDPs","created":"2026-05-23","cited_by_count":0,"area":"deeprl"},{"id":"2607.06935","title":"Mathematical methods of reinforcement learning","created":"2026-07-08","cited_by_count":0,"area":"deeprl"},{"id":"2607.16999","title":"Counterfactual Shapley Credit Assignment","created":"2026-07-18","cited_by_count":0,"area":"deeprl"},{"id":"2609.35525","title":"Deep Epistemic Value Functions for Optimistic Exploration","created":"2026-09-28","cited_by_count":0,"area":"deeprl"}],"next_cursor":null}