RESUME VERACITY ENCODER
RESUME VERACITY ENCODER is an encoder-based NLP model designed to detect exaggerated or potentially false claims in resumes using semantic consistency and experience–skill alignment.
The model is intended for HR technology platforms, recruiters, hiring managers, and background verification systems.
🎯 Objective
Resume screening today suffers from:
- Skill exaggeration
- Inflated years of experience
- Buzzword stuffing
- Misaligned role claims
RESUME VERACITY ENCODER automates the first layer of resume verification by scoring the credibility of claims using natural language understanding.
🚀 Key Features
- Encoder-based text-classification model
- Detects truthful vs exaggerated claims
- Semantic claim extraction from resumes
- Hugging Face–ready training & inference
- Modular, production-grade architecture
- Apache-2.0 licensed
🧠 Model Details
Model Name: RESUME VERACITY ENCODER
Architecture: Encoder (BERT-based)
Pipeline Tag: text-classification
Task: Resume claim veracity detection
📜 License
Apache License 2.0