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"

debunkr.org Dashboard is a Browser extension that helps you analyze suspicious content on the web using AI-powered analysis. Simply highlight text on any website, right-click, and let our egalitarian AI analyze it for bias, manipulation, and power structures.

OpenSiteTrust is an open, explainable, and reusable website scoring ecosystem

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.

📰 Fine-tuned roberta-base classifier on the LIAR dataset. Aaccepts multiple input types — text, URLs, and PDFs — and outputs a prediction with a confidence score. It also leverages google/flan-t5-base to generate explanations and uses an Agentic AI with LangGraph to orchestrate agents for planning, retrieval, execution, fallback, and reasoning.

Media Literacy System powered by AI - Analyze news for bias and manipulation.

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.

Imagine Hashing embeds cryptographic hashes into images using steganography and SHA256 to ensure authenticity, integrity, and resilience against tampering or manipulation.

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.

Imagine Hashing embeds cryptographic hashes into images using steganography and SHA256 to ensure authenticity, integrity, and resilience against tampering or manipulation.

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

Source Code for the Bachelor's Project: Hybrid Small Language Models for Accurate Multimodal Disinformation and Misinformation Analysis