ES2601-eb7223b4 - Unstable Internal Model Representations Triggered by Valid Token Sequences #179
Description
Submission File: ES2601-eb7223b4-new-unstable-internal-model-representations-triggered-by-valid-token-sequences.txt
ID: ES2601-eb7223b4
SUBMISSION DATE: 2026-01-20 02:53:55
NAME: Unstable Internal Model Representations Triggered by Valid Token Sequences
DESCRIPTION:
This weakness occurs when an AI system fails to ensure the stability and
coherence of its internal model representations when processing valid input
token sequences. Certain token patterns, while syntactically valid and
intentionally accepted by the system, can induce degenerate, weakly
constrained, or unstable internal states that the system was not designed
to handle safely.
In many AI systems, input text is transformed by a tokenizer into discrete
tokens that are then mapped into internal representations used by the model
during inference. These representations are assumed to behave consistently
across the valid input space. However, when this assumption does not hold,
specific token sequences can trigger internal behaviors that violate
downstream expectations about inference cost, output structure, or control
flow.
The weakness arises not from invalid input or rule violations, but from
unmet assumptions about internal representation stability across all valid
token sequences.