2 papers
cs.AI2025
Predictive Coding Enhances Meta-RL To Achieve Interpretable Bayes-Optimal Belief Representation Under Partial Observability
Po-Chen Kuo, Han Hou, Will Dabney +1
Learning a compact representation of history is critical for planning and generalization in partially observable environments. While meta-reinforcement learning (RL) agents can att…
cs.LG2025
xbench: Tracking Agents Productivity Scaling with Profession-Aligned Real-World Evaluations
Kaiyuan Chen, Yixin Ren, Yang Liu +30
We introduce xbench, a dynamic, profession-aligned evaluation suite designed to bridge the gap between AI agent capabilities and real-world productivity. While existing benchmarks…