Localizing a Self-Referential Register to a Single Expert in a Mixture-of-Experts Model, and Why It Does Not Transfer

Localizing a Self-Referential Register to a Single Expert in a Mixture-of-Experts Model, and Why It Does Not Transfer. Preprint, version 1.1.0 (June 2026). Not peer reviewed. Mixture-of-experts routing emits a discrete, per-token record of which experts fire, a signal unusually legible for interpretability, yet single experts are rarely tied to a specific functional role, least of all one resembling a model's self-report. We characterize one routed expert, Expert 114 at layer 14 of Qwen3.5-35B-A3B, as a linear detector of a generated self-referential register, and bound what it does. Across held-out, bottom-up, and cross-model tests we show that (1) its recovered router direction separates self-referential generations from lexically matched controls with no overlap (Cohen's d = 3.88); (2) a blind, prompt-independent auto-interpreter recovers the same register at AUC 0.94, broadening it from self-reference to an abstract reflective and philosophical one; (3) the detector is a readout with only weak, conditional control: residual injection induces the register, yet gate suppression does not remove it, and it is invariant to whether the model affirms or denies an interior; and (4) the role is model-specific, failing to transfer to the larger Qwen3.5-122B-A10B. We release the prompts, scripts, and provenance under the MIT license. This deposit is the paper-scoped artifact bundle: the paper (ACL-style LaTeX source and built PDF), per-run summaries, analysis scripts, prompt and class manifests, checksums, plots, and source journals. Raw activation/router tensors are kept out of version control and archived separately (see ZENODO-TENSORS.md).

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-29
DOI
https://doi.org/10.5281/zenodo.21016030
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Localizing a Self-Referential Register to a Single Expert in a Mixture-of-Experts Model, and Why It Does Not Transfer

Jeffrey W. Shorthill
Zenodo (CERN European Organization for Nuclear Research)
Explainable Artificial Intelligence (XAI)
preprint

Localizing a Self-Referential Register to a Single Expert in a Mixture-of-Experts Model, and Why It Does Not Transfer

Jeffrey W. Shorthill
preprint en

Abstract

Localizing a Self-Referential Register to a Single Expert in a Mixture-of-Experts Model, and Why It Does Not Transfer. Preprint, version 1.1.0 (June 2026). Not peer reviewed. Mixture-of-experts routing emits a discrete, per-token record of which experts fire, a signal unusually legible for interpretability, yet single experts are rarely tied to a specific functional role, least of all one resembling a model's self-report. We characterize one routed expert, Expert 114 at layer 14 of Qwen3.5-35B-A3B, as a linear detector of a generated self-referential register, and bound what it does. Across held-out, bottom-up, and cross-model tests we show that (1) its recovered router direction separates self-referential generations from lexically matched controls with no overlap (Cohen's d = 3.88); (2) a blind, prompt-independent auto-interpreter recovers the same register at AUC 0.94, broadening it from self-reference to an abstract reflective and philosophical one; (3) the detector is a readout with only weak, conditional control: residual injection induces the register, yet gate suppression does not remove it, and it is invariant to whether the model affirms or denies an interior; and (4) the role is model-specific, failing to transfer to the larger Qwen3.5-122B-A10B. We release the prompts, scripts, and provenance under the MIT license. This deposit is the paper-scoped artifact bundle: the paper (ACL-style LaTeX source and built PDF), per-run summaries, analysis scripts, prompt and class manifests, checksums, plots, and source journals. Raw activation/router tensors are kept out of version control and archived separately (see ZENODO-TENSORS.md).

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Explainable Artificial Intelligence (XAI)
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.