Towards Robust Fact-Checking: A Multi-Agent System with Advanced Evidence Retrieval

🔍 ABCheckers 💬 is a data-driven project that analyzes Twitter discourse to uncover misinformation around 🇵🇭 inflation and the weakening peso, empowering users with contextual insights.

Tathya (तथ्य, "truth") is an Agentic fact-checking system that verifies claims using multiple sources including Google Search, DuckDuckGo, Wikidata, and news APIs. It provides structured analysis with confidence scores, detailed explanations, and transparent source attribution through a modern Streamlit interface and FastAPI backend.

Code associated with the NAACL 2025 paper "COVE: COntext and VEracity prediction for out-of-context images"

🔍 Verificador de Fake News: Uma ferramenta web moderna que utiliza IA (Google Gemini) para analisar e detectar desinformação em tempo real. Desenvolvido com JavaScript, Bootstrap 5 e PWA para promover uma comunicação mais consciente e baseada em fatos.

This project implements a complete NLP pipeline for Persian tweets to classify topics and detect fake news. Using a Random Forest classifier, it compares tweet content with trusted news sources, achieving 70% accuracy in fake news detection.

Watermarking System | AI-Generated Media Detection A system for detecting and flagging AI-generated images using ML and steganography. Ensures authenticity with imperceptible, resilient watermarks embedded at creation.

An advanced AI-powered fake news detection system that verifies text, images, and social media posts using Gemini AI, FastAPI, and Next.js. Includes a modern web interface, a lightweight Streamlit app, and a Chrome extension for real-time fake content detection. Built to combat misinformation with explainable AI results and contextual source links.

Code for the paper "Evaluating AI capabilities in detecting conspiracy theories on YouTube".