NRR-Phi: Text-to-State Mapping for Ambiguity Preservation in LLM Inference

ArXi:2601.19933v5 Announce Type: replace-cross Large language models exhibit a systematic tendency toward early semantic commitment: given ambiguous input, they collapse multiple valid interpretations into a single response before sufficient context is available. This premature collapse discards information that may prove essential as dialogue evolves. We present a formal framework for text-to-state mapping (phi: T -> S) that transforms natural language into a non-collapsing state space where multiple interpretations coexist.