Share the Symbol, Not the Vector: Training-Free Fact Communication Across Language Models
SYNC lets heterogeneous language models share facts via word indices, reaching up to 98.3% without extra training.
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SYNC lets heterogeneous language models share facts via word indices, reaching up to 98.3% without extra training.
Entropy and CKA layer selection improves EAGLE3-style speculative decoding over the fixed [2, N//2, N-3] baseline.
Interpretability study traces how Qwen, Llama, and Gemma route query information and internal knowledge across layers when answering questions.
Researchers propose auditing LLM bias via relative hidden-state representations, detecting bias increases with 3-50x less compute than output-level benchmarks.
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