4 papers
Rationality Measurement and Theory for Reinforcement Learning Agents
Kejiang Qian, Amos Storkey, Fengxiang He
This paper proposes a suite of rationality measures and associated theory for reinforcement learning agents, a property increasingly critical yet rarely explored. We define an acti…
In LLM Reasoning, there is Irrationality on top of Value Misalignment
Kejiang Qian, Fengxiang He
Significant progress has been made in aligning LLMs with target value functions. We argue that, even when an LLM has been well aligned in (post-)training, it may still fail to maxi…
PRISM: Parallel Reward Integration with Symmetry for MORL
Finn van der Knaap, Kejiang Qian, Zheng Xu +1
This work studies heterogeneous Multi-Objective Reinforcement Learning (MORL), where objectives can differ sharply in temporal frequency. Such heterogeneity allows dense objectives…
DeXposure: A Dataset and Benchmarks for Inter-protocol Credit Exposure in Decentralized Financial Networks
Wenbin Wu, Kejiang Qian, Alexis Lui +5
We curate the DeXposure dataset, the first large-scale dataset for inter-protocol credit exposure in decentralized financial networks, covering global markets of 43.7 million entri…