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Download README.md from Categorica/XLM-R-Indic-Hardened: direct link, hf CLI and curl.
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632 Bytes
metadata
language: multilingual
tags:
- fact-checking
- adversarial-robustness
- indic
license: mit
Defended Indic Fact-Checking Model
This model has been fine-tuned and defended against adversarial attacks using the Unified Adversarial Testing Framework.
Model Details
- Language: multilingual
- Task: Fact-Checking / Claim Verification
- Defenses Applied: Product of Experts (PoE), Debiased Focal Loss (DFL)
Intended Use
Designed to verify claims in regional Indian languages with high robustness against adversarial manipulations (e.g., character swapping, multi-hop temporal logic).