Yuchen Liu
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The paper proposes AdaBFL, a multi-layer defensive adaptive aggregation method that enhances Byzantine-robust federated learning by adaptively adjusting defense weights to counter complex poisoning attacks.
The paper introduces Graph-Distance Contribution Reward (GDCR) and Step Advantage Policy Optimization (SAPO) to provide fine-grained, step-level credit assignment for agentic search by modeling world knowledge as a latent graph.
Papers
Beyond Trajectory Rewards: Step-level Credit Assignment for Agentic Search via Graph Modeling
Yuchen Liu, Yingjie Feng, Lixiong Qin, Jiasi Chen +4 more
The paper introduces Graph-Distance Contribution Reward (GDCR) and Step Advantage Policy Optimization (SAPO) to provide fine-grained, step-level credit assignment for agentic search by modeling world…