Skip to content
#small language model Open access

The Tailor's Reading

Sep 2026 · Zenodo (CERN European Organization for Nuclear Research)

Abstract

A feature of a sparse-autoencoder dictionary is published with one natural-language label, written by one language model from the passages that most excite the feature in one corpus. That label is a reading, and its provenance, the explainer, the explainer's system prompt, the corpus, and the model through which the corpus was run, is usually left unstated. We propose recording the provenance with every label and adding, for every feature, a second label written under a different and declared provenance, kept beside the published one rather than replacing it. We demonstrate this on Google DeepMind's Gemma Scope 2 dictionary for layer 31 of gemma-3-27b (262,144 features), read through a small fine-tuned adapter that reproduces one author's writing of 2012, with a system prompt built from that author's own vocabulary. The same feature then carries Neuronpedia's label creation and genesis stories and, under our provenance, Elohim's "Let there be": the creating Word. With the labels in hand we read seven texts step by step, three diaries and a memoir generated by the model family, a chat, Shakespeare's sonnets and Hamlet's speeches, and ask whether individual features stay active across consecutive steps longer than chance. The test uses a per-feature permutation test, two family-level null models (whole-order permutation and a fixed-margin null), and a replication under a wrong preceding context. Five of the seven texts show more persisting features than the maximum of either null; the sonnets do not at the main threshold, and the seventh, a twenty-entry diary, reaches only one of the two. What persists is where a text changes and what it carries: the fine-tuned diary's first movement on the author's coinages and its collapse at entry 28; the rooms, the vessel and the gap of a second persona's diary in the order she wrote them; Hamlet's forged commission in its Latinate register; in the sonnets the traditional groupings, on which nine of twenty-three persisting features have their longest run against six by chance, read as their arguments; and in the chat a rupture and a return measured, 510 features of address that go dark for sixteen messages and 458 that come back. We also define a glued space over the features of a text, a homotopy colimit of one complex per step glued along what consecutive steps share, whose first Betti number counts returns of co-firing pairs; it tracks a direct count of pair returns nearly one to one. Labels cost $0.002–$0.02 each. The system prompt is authored; the labels are not scored against held-out text; a label under a provenance answers only what the feature means under that provenance. Full HTML text: https://icra.tanazur.org/papers/the-tailors-reading/ — ICRA pre-print series: https://icra.tanazur.org/

View source

Similar papers

#small language model Dataset Open access Oct 2026

Socratic guiding questions in synthetic arithmetic data: matched LoRA runs (revision v2)

Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...

O'Grady, Jake, Gürhan, Asena Isik, Chee, Fong Ting et al. · 465 citations
#computer vision Open access Jun 2016

Software Development in Startup Companies: The Greenfield Startup Model

The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.

Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al. · 178 citations · ⚡14
#computer vision Open access Oct 2016

Software Startups - A Research Agenda

Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.

M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al. · 157 citations · ⚡17
#machine learning Review Open access Oct 2016

“Failures” to be celebrated: an analysis of major pivots of software startups

This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.

Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al. · 127 citations · ⚡15
#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#large language models Review Open access Nov 2020

Status of the WHO recommended timing and frequency of antenatal care visits in Northern Bangladesh

Objective There is dearth of information on the timeliness of antenatal care (ANC) uptake. This study aimed to determine the timely ANC uptake by a medically trained provider (MTP) as per the World Health Organization (WHO) recommendations and the country guideline. Methods Cross-sectional survey was done with 2,731 wo...

B. Sarker, Musfikur Rahman, T. Rahman et al. · 89 citations · ⚡7

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.