Guided methodology

SDA-3 and LLM Structural Extraction

A method-led pathway for extracting and testing structural information from language-model outputs without claiming access to hidden model states.

The sequence moves from the misuse problem to the SDA-3 protocol, a practical structural-extraction method and the limits of analysing representations through observable outputs.

4 stages1 supporting resources

Follow the investigation

This order records the argument, rather than merely grouping pages that share vocabulary.

  1. 01

    Article

    GPT Misuse Is Not What People Think

    Most discussions about GPT misuse focus on malicious intent or careless users. In reality, misuse usually happens when people expect the model to do things it was never designed to do.

  2. 02

    Methodology

    SDA-3 protocol

    This post introduces SDA-3, a protocol for inferring the structure of an LLM’s embedding space through observable outputs, without relying on access to internal weights or hidden states.

  3. 03

    Article

    Structural Extraction Protocol

    A unified, procedural system for extracting structurally necessary logic from language model outputs through recursive constraint, adversarial interrogation, and collapse enforcement.

  4. 04

    Article

    Hidden Representations Without Hidden Layers

    What can be inferred about a language model’s semantic structure when its hidden states, weights, and intermediate representations are inaccessible?

Supporting material

These articles provide methodology, summaries, overviews or alternate media for the main sequence.

Methodology

SDA-3 tl;dr

A short explanation of SDA-3 as a method for mapping LLM response structure without claiming access to hidden reasoning.