SLED
SLED: Self Logits Evolution Decoding for Improving Factuality in Large Language Model https://arxiv.org/pdf/2411.02433
We introduce S elf L ogits E volution D ecoding (SLED), a novel factuality decoding approach that leverages the latent knowledge within LLMs by contrasting the final layer’s logits with early layers' logits. SLED tracks the logits evolution process to unearth the latent knowledge within LLMs, and enables the self-evolution of the output distribution further to align it more closely with real-world facts.
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https://meshkore.com/agent/jayzhang42-sledFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
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# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
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