Key papers

• Large-Scale Portfolio Optimization Problem Under Cardinality Constraint With Enhanced Multi-Objective Evolutionary Algorithms (2026)
  Danial Ramezani et al.
  5.01
• Spectral-Informed Neural Networks Outperform Spectral Methods in High-dimensional PDEs (2026)
  Tianchi Yu et al.
  4.39
• Generalized Kalman filter based temporal difference reinforcement learning (2026)
  Vasos Arnaoutis et al.
  4.39
• DeepSeekMath Meets Order Book: Group-Aware Policy Optimization for High-Frequency Directional Trading (2026)
  Sayak Charabarty et al.
  4.27
• FLAG-Trader: Fusion LLM-Agent with Gradient-based Reinforcement Learning for Financial Trading (2025)
  Guojun Xiong et al.
  3.59
• Cell-o1: Training LLMs to Solve Single-Cell Reasoning Puzzles with Reinforcement Learning (2025)
  Yin Fang et al.
  2.87
• Revisiting Ensemble Methods for Stock Trading and Crypto Trading Tasks at ACM ICAIF FinRL Contest 2023-2024 (2025)
  Nikolaus Holzer et al.
  2.60
• TT-DAC-PS: Twin-Target Deterministic Actor-Critic with Policy Smoothing for Optimal Trade Execution (2026)
  Ilia Zaznov et al.
  1.94
• gym-invmgmt: An Open Benchmarking Framework for Inventory Management Methods (2026)
  Reza Barati and Qinmin Vivian Hu
  1.89
• From Feedback Loops to Policy Updates: Reinforcement Fine-Tuning for LLM-Based Alpha Factor Discovery (2026)
  Lingzhe Zhang et al.
  1.89
• Discrete Flow Matching Policy Optimization (2026)
  Maojiang Su et al.
  1.83
• Reinforcement Learning with LLM-Guided Action Spaces for Synthesizable Lead Optimization (2026)
  Tao Li et al.
  1.83
• When Valid Signals Fail: Regime Boundaries Between LLM Features and RL Trading Policies (2026)
  Zhengzhe Yang
  1.83
• Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis (2026)
  Zhisong Qiu et al.
  1.83
• Selection as Power: Constrained Reinforcement for Bounded Decision Authority (2026)
  Jose Manuel de la Chica Rodriguez and Juan Manuel Vera D\'iaz
  1.78
• Realistic Market Impact Modeling for Reinforcement Learning Trading Environments (2026)
  Lucas Riera Abbade and Anna Helena Reali Costa
  1.78
• The Enhanced Physics-Informed Kolmogorov-Arnold Networks: Applications of Newton's Laws in Financial Deep Reinforcement Learning (RL) Algorithms (2026)
  Trang Thoi et al.
  1.72
• Harnessing Implicit Cooperation: A Multi-Agent Reinforcement Learning Approach Towards Decentralized Local Energy Markets (2026)
  Nelson Salazar-Pena et al.
  1.72
• MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamics (2026)
  Zhuofan Shi et al.
  1.67
• Reinforcement Learning of Large Language Models for Interpretable Credit Card Fraud Detection (2026)
  Cooper Lin et al.
  1.67
• Case-Guided Sequential Assay Planning in Drug Discovery (2026)
  Tianchi Chen et al.
  1.67
• Natural-gas storage modelling by deep reinforcement learning (2025)
  Tiziano Balaconi et al.
  1.56
• Fitting Reinforcement Learning Model to Behavioral Data under Bandits (2025)
  Hao Zhu et al.
  1.56
• Hybrid LSTM and PPO Networks for Dynamic Portfolio Optimization (2025)
  Jun Kevin et al.
  1.56
• Optimize Flip Angle Schedules In MR Fingerprinting Using Reinforcement Learning (2025)
  Shenjun Zhong et al.
  1.56
• Diffusion-Augmented Reinforcement Learning for Robust Portfolio Optimization under Stress Scenarios (2025)
  Himanshu Choudhary et al.
  1.50
• DeepAries: Adaptive Rebalancing Interval Selection for Enhanced Portfolio Selection (2025)
  Jinkyu Kim et al.
  1.50
• Optimized Renewable Energy Planning MDP for Socially-Equitable Electricity Coverage in the US (2025)
  Riya Kinnarkar et al.
  1.44
• Trading-R1: Financial Trading with LLM Reasoning via Reinforcement Learning (2025)
  Yijia Xiao et al.
  1.44
• Deep Reinforcement Learning in Factor Investment (2025)
  Junlin Liu
  1.44
• Laser Scan Path Design for Controlled Microstructure in Additive Manufacturing with Integrated Reduced-Order Phase-Field Modeling and Deep Reinforcement Learning (2025)
  Augustine Twumasi et al.
  1.28
• Leveraging Partial SMILES Validation Scheme for Enhanced Drug Design in Reinforcement Learning Frameworks (2025)
  Xinyu Wang et al.
  1.22
• CiRL: Open-Source Environments for Reinforcement Learning in Circular Economy and Net Zero (2025)
  Federico Zocco et al.
  1.22
• RLDBF: Enhancing LLMs Via Reinforcement Learning With DataBase FeedBack (2025)
  Weichen Dai et al.
  1.17
• Deep Reinforcement Learning Algorithms for Option Hedging (2025)
  Andrei Neagu et al.
  1.17
• Reinforcement learning framework for the mechanical design of microelectronic components under multiphysics constraints (2025)
  Siddharth Nair et al.
  1.17
• A Deep Reinforcement Learning Approach to Automated Stock Trading, using xLSTM Networks (2025)
  Faezeh Sarlakifar et al.
  1.11
• Predicting Liquidity-Aware Bond Yields using Causal GANs and Deep Reinforcement Learning with LLM Evaluation (2025)
  Jaskaran Singh Walia et al.
  1.06
• Data-driven inventory management for new products: An adjusted Dyna-$Q$ approach with transfer learning (2025)
  Xinye Qu et al.
  1.00
• Dynamic Portfolio Optimization via Augmented DDPG with Quantum Price Levels-Based Trading Strategy (2025)
  Runsheng Lin et al.
  1.00
• Inverse Reinforcement Learning via Convex Optimization (2025)
  Hao Zhu et al.
  1.00
• Learning Optimal Solutions via an LSTM-Optimization Framework (2022)
  Dogacan Yilmaz et al.
  —
• Basal-Bolus Advisor for Type 1 Diabetes (T1D) Patients Using Multi-Agent Reinforcement Learning (RL) Methodology (2023)
  Mehrad Jaloli et al.
  —
• JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading (2023)
  Sascha Frey et al.
  —
• Gray-box Adversarial Attack of Deep Reinforcement Learning-based Trading Agents (2023)
  Foozhan Ataiefard et al.
  —
• Applying Reinforcement Learning to Option Pricing and Hedging (2023)
  Zoran Stoiljkovic
  —
• Logic-Q: Improving Deep Reinforcement Learning-based Quantitative Trading via Program Sketch-based Tuning (2023)
  Zhiming Li et al.
  —
• A Lightweight Calibrated Simulation Enabling Efficient Offline Learning for Optimal Control of Real Buildings (2023)
  Judah Goldfeder et al.
  —
• Reinforcement Learning for Solving Stochastic Vehicle Routing Problem (2023)
  Zangir Iklassov et al.
  —
• Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications? (2023)
  Rex Chen et al.
  —
• Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools (2023)
  Wentao Zhang et al.
  —
• Controlgym: Large-Scale Control Environments for Benchmarking Reinforcement Learning Algorithms (2023)
  Xiangyuan Zhang et al.
  —
• Extreme Event Prediction with Multi-agent Reinforcement Learning-based Parametrization of Atmospheric and Oceanic Turbulence (2023)
  Rambod Mojgani and Daniel Waelchli and Yifei Guan and Petros Koumoutsakos and Pedram Hassanzadeh
  —
• Can Reinforcement Learning support policy makers? A preliminary study with Integrated Assessment Models (2023)
  Theodore Wolf and Nantas Nardelli and John Shawe-Taylor and Maria Perez-Ortiz
  —
• Multi-Objective Reinforcement Learning-based Approach for Pressurized Water Reactor Optimization (2023)
  Paul Seurin and Koroush Shirvan
  —
• Synergistic Formulaic Alpha Generation for Quantitative Trading based on Reinforcement Learning (2024)
  Hong-Gi Shin et al.
  —
• Advancing ECG Diagnosis Using Reinforcement Learning on Global Waveform Variations Related to P Wave and PR Interval (2024)
  Rumsha Fatima et al.
  —
• De novo Drug Design using Reinforcement Learning with Multiple GPT Agents (2024)
  Xiuyuan Hu et al.
  —
• Learning and Calibrating Heterogeneous Bounded Rational Market Behaviour with Multi-Agent Reinforcement Learning (2024)
  Benjamin Patrick Evans et al.
  —
• Brain-Like Replay Naturally Emerges in Reinforcement Learning Agents (2024)
  Jiyi Wang et al.
  —