Researchers introduced Belief-Trajectory Energy (BTE), a model-grounded measure that characterizes an input through the trajectory of prediction revisions across Transformer layers rather than only the final output. The work addresses the fact that large language models progressively revise predictions layer by layer while typically only the final output is observed.
Large language models (LLMs) progressively revise their predictions across Transformer layers, yet we typically observe only the final output, discarding the trajectory through which it is formed. We introduce Belief-Trajectory Energy(BTE), a model-grounded measure that characterizes an input throug
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