1. 9.9 A Q-learning Approach for Adherence-Aware Recommendations
   • Authors: Ioannis Faros, Aditya Dave, Andreas A. Malikopoulos
   • Reason: Direct application of reinforcement learning with real-world impact in scenarios involving high-stakes decisions.
2. 9.5 Offline Prompt Evaluation and Optimization with Inverse Reinforcement Learning
   • Authors: Hao Sun
   • Reason: Application of Inverse-RL to a novel problem of prompt optimization.
3. 9.3 Reasoning with Latent Diffusion in Offline Reinforcement Learning
   • Authors: Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella, John Dolan, Jeff Schneider, Glen Berseth
   • Reason: Focuses on major problem in offline RL of effectively stitching suboptimal trajectories.
4. 9.1 Attention Loss Adjusted Prioritized Experience Replay
   • Authors: Zhuoying Chen, Huiping Li, Rizhong Wang
   • Reason: Improvement on Prioritized Experience Replay, a pivotal technique in deep reinforcement learning.
5. 9.0 Safe Reinforcement Learning with Dual Robustness
   • Authors: Zeyang Li, Chuxiong Hu, Yunan Wang, Yujie Yang, Shengbo Eben Li
   • Reason: Addressing the crucial yet challenging issue of creating RL agents that are both safe and robust.