activity
20232026
most citedAI Agent as Urban Planner: Steering Stakeholder Dynamics in Urban Planning via Consensus-based Multi-Agent Reinforcement Learning

6 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2025

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…

cs.AI20236 cited

AI Agent as Urban Planner: Steering Stakeholder Dynamics in Urban Planning via Consensus-based Multi-Agent Reinforcement Learning

Kejiang Qian, Lingjun Mao, Xin Liang +5

In urban planning, land use readjustment plays a pivotal role in aligning land use configurations with the current demands for sustainable urban development. However, present-day u…