Network transparency for a local LLM: Qwen3-14B v2 NT — a LoRA that announces and reports every network connection, with two disclosed shortfalls / Trasparenza di rete per un LLM locale: Qwen3-14B v2 NT

LoRA adapter for Qwen3-14B v2 that announces before and reports after every network connection (host, country, direction). Recall 99.7%, country/direction 100%, pre-announcement 99.3% (450 dev runs); identity 98% vs 76%; GSM8K 94.9 vs 94.7; ARC-it 90.5 vs 90.6. Limitations disclosed: IFEval 83.5 vs 83.9 (−0.4 pt, p=0.87, not significant) and leak rate 1.11% (5/450) vs a pre-registered ≤1% gate, 95% Wilson CI [0.48%, 2.57%]. Published as a documented exception. Articles in Italian and English. Weights: https://huggingface.co/odelpa/qwen14-scienziato-v2-nt · Code/eval: https://github.com/usergdp136/qwen14-scienziato-v2-nt

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-04
DOI
https://doi.org/10.5281/zenodo.23950985
Primary Topic
Adversarial Robustness in Machine Learning
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Network transparency for a local LLM: Qwen3-14B v2 NT — a LoRA that announces and reports every network connection, with two disclosed shortfalls / Trasparenza di rete per un LLM locale: Qwen3-14B v2 NT

Giovanni Del Papa
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
preprint

Network transparency for a local LLM: Qwen3-14B v2 NT — a LoRA that announces and reports every network connection, with two disclosed shortfalls / Trasparenza di rete per un LLM locale: Qwen3-14B v2 NT

Giovanni Del Papa
preprint en

Abstract

LoRA adapter for Qwen3-14B v2 that announces before and reports after every network connection (host, country, direction). Recall 99.7%, country/direction 100%, pre-announcement 99.3% (450 dev runs); identity 98% vs 76%; GSM8K 94.9 vs 94.7; ARC-it 90.5 vs 90.6. Limitations disclosed: IFEval 83.5 vs 83.9 (−0.4 pt, p=0.87, not significant) and leak rate 1.11% (5/450) vs a pre-registered ≤1% gate, 95% Wilson CI [0.48%, 2.57%]. Published as a documented exception. Articles in Italian and English. Weights: https://huggingface.co/odelpa/qwen14-scienziato-v2-nt · Code/eval: https://github.com/usergdp136/qwen14-scienziato-v2-nt

Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
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.

Laika access coming soon