LC-ERD frames LLM self-alignment as latent structure mining via a Variational Logic Potential and Multi-Agent Value Decomposition to provide granular, logic-consistent supervision.
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SAL is a spike-timing-based local learning rule that aligns feedback weights to forward weights in spiking networks by exploiting noise and Hebbian/anti-Hebbian plasticity to recover the true gradient.
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LC-ERD: Mining Latent Logic for Self-Evolving Reasoning via Consistency-Regulated Reward Decomposition
LC-ERD frames LLM self-alignment as latent structure mining via a Variational Logic Potential and Multi-Agent Value Decomposition to provide granular, logic-consistent supervision.
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Spike-based alignment learning solves the weight transport problem
SAL is a spike-timing-based local learning rule that aligns feedback weights to forward weights in spiking networks by exploiting noise and Hebbian/anti-Hebbian plasticity to recover the true gradient.