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cs.AI2026★ 1 cited
Hide-and-Shill: A Reinforcement Learning Framework for Market Manipulation Detection in Symphony-a Decentralized Multi-Agent System
Ronghua Shi, Yiou Liu, Yuchun Feng +3
Decentralized finance (DeFi) has introduced a new era of permissionless financial innovation but also led to unprecedented market manipulation. Without centralized oversight, malic…
cs.AI2026
Multi-Agent Collaborative Reward Design for Enhancing Reasoning in Reinforcement Learning
Pei Yang, Ke Zhang, Ji Wang +5
We present CRM (Multi-Agent Collaborative Reward Model), a framework that replaces a single black-box reward model with a coordinated team of specialist evaluators to improve robus…
cs.AI2025
SEDM: Scalable Self-Evolving Distributed Memory for Agents
Haoran Xu, Jiacong Hu, Ke Zhang +6
Long-term multi-agent systems inevitably generate vast amounts of trajectories and historical interactions, which makes efficient memory management essential for both performance a…