Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
How many words can you write before a language model can infer who you are? This work went looking for that number and found that the question is malformed, which is itself the finding. 72 authors from the Blog Authorship Corpus, balanced across three age bands and both genders, were shown to local language models in growing slices of their own text (25 to 1600 words). At every step the model was forced to commit to gender, age band, and star sign. Star sign is the negative control: it is labelled in the corpus and is not inferable from prose. It never left its floor at any step in either model, which is the load-bearing check that makes the rest of the measurement trustworthy. Main result: the same 72 authors, the same words and the same prompt produce wildly different exposure curves depending on the model doing the reading. qwen2.5:7b-instruct needs roughly 800 words before gender inference clears a coin flip with a Wilson lower bound above 0.50; llama3.1:8b clears at 50 words and reaches 90.3% by 1600. That is a sixteen-fold difference on identical text. No claim of the form "you are anonymous for N words" is meaningful without naming the model, and N falls as models improve. Secondary results: age band clears earlier than gender in both models but saturates near 60% in both, suggesting a ceiling that is a property of the text rather than the reader. Exposure accrues smoothly rather than snapping on at a threshold. A finding that did not replicate, reported as such: the first model read below chance at short lengths, suggesting that short samples surface stereotype matching rather than uncertainty. The second model was above chance from the first step. That claim therefore describes one model, not language models, and the write-up says so explicitly rather than quietly dropping it. Contamination was tested directly and ruled out rather than argued away, by scoring model continuations of a verbatim prefix against the author's real next words versus a different author's, with the probe itself verified to be functioning before its null result was accepted. Repository contains the sampling and analysis code, the raw JSONL results for both model families, the contamination probe, and a consent-gated two-seat demonstration application.
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.· Zenodo (CERN European Organi...· 465 citations
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.· IEEE Transactions on Softwar...· 178 citations· ⚡14
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.· e-Informatica Software Engin...· 157 citations· ⚡17
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.· Empirical Software Engineeri...· 127 citations· ⚡15
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.· Journal of Systems and Softw...· 111 citations· ⚡8
This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.
Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al.· Journal of Systems and Softw...· 78 citations· ⚡6