Recent papers on achieved false detection improvement room

Sorted by publication year (newest first) via OpenAlex. List regenerates every 24h.

1. B0-SIF: Multi-AI Verification Protocol for Semantic Noise ReductionB0-SIF (Base-Zero Semantic Integrity Framework) is an open-source protocol for detecting and eliminating semantic noise in large language model outputs through cross-platform validation. RESEARCH CONTRIBUTIONS: • Multi-AI verification methodology across 4 major systems (Gemini, Grok, GPT-4, Claude) • RON pipeline (Reduction, Purification, Normalization) achieving 71-85% noise reduction • SHA-256 audit trail system for output verification • Python implementation with semantic similarity detector • 10 annotated test cases with reproducible results KEY FINDINGS: Models exhibit 71-85% "hallucination overhead" when generating narrative responses versus extracting pure facts. Cross-model validation reduces false positives to <5%. VERSION HISTORY: • v3.0 (Jan 2026): Research-focused release optimized for AI safety community • v2.1 (Jan 2026): Original whitepaper with commercial framework [archived] REPRODUCIBILITY: Complete dataset includes prompts, raw outputs, verification scripts, and test articles. All code and documentation available for independent validation. APPLICATIONS: AI safety research, hallucination detection, fact-checking systems, cross-model benchmarking, semantic integrity verification

   2026 · Open MIND · Mirga, David

   2026

2. Hybrid Deep-Ensemble Learning for Cybersecurity: A Multi-Dataset Framework Achieving High Precision and Minimal False Positives in Attack Detection

   2025 · International journal of intelligent engineering and systems

   2025

3. Preventing Ransomware Damages Using in-Operation Off-Site Backup to Achieve a 10⁻⁸ False-Negative Miss-Detection Rate

   2025 · Fujinoki, Hiroshi, Towell, Alexander A., Thota, Vamshi Anirudh

   2025

4. Achieving Zero False Negatives: Optimizing Anomaly Detection with Genetic Neural Architecture Search

   2025 · Communications in computer and information science · Najem, Rabie, Benjelloun, Mohammed

   2025

5. Achieving a Zero False Negative Rate Unsupervised Detection on Controller Area Network (CAN) Bus with LSTM-Based Autoencoder

   2023 · Afify, Karim Kamal, Abbas, Hazem M., Abdullah, Bassem A.

   2023

6. Achieving Efficient Detection Against False Data Injection Attacks in Smart Grid

   2017 · IEEE Access · Xu, Ruzhi, Wang, Rui, Guan, Zhitao et al.

   2017

7. Achieving High Reliability in SAODV by Decreasing False Positive Blackhole Detection Rate in MANET

   2015 · International Journal of Scientific Engineering and Research · Chawla, Yudhister, Shekhawat, Hardayal Singh

   2015