Bo Jin
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The paper proposes a novel temporal and structural credit assignment framework to efficiently optimize multi-agent LLM systems by decomposing the error signal and using targeted, discrete gradient updates.
The paper introduces Singularity-aware Adam (S-Adam), a novel optimizer that stabilizes deep learning training in non-smooth loss landscapes by dynamically damping updates based on local geometric instability.
Papers
Unifying Temporal and Structural Credit Assignment in LLM-Based Multi-Agent Prompt Optimization
Wenwu Li, Yuran Song, Mingze Zhao, Bo Jin +1 more
The paper proposes a novel temporal and structural credit assignment framework to efficiently optimize multi-agent LLM systems by decomposing the error signal and using targeted, discrete gradient upd…