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

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

FailSafe: An autonomous fact-checking framework leveraging Multi-Agent LLMs and Structured Argumentation Graphs (SAG) to verify claims with deep-web retrieval and reasoning.

This repository provides scripts and workflows for translating fact-checking datasets and automating claim classification using large language models (LLMs).

Code associated with the preprint: "M4FC: a Multimodal, , Multilingual, Multicultural, Multitask real-world Fact-Checking Dataset"

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.

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.

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

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.

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

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

🛡️ WonderAI: Your digital shield against fake news. Real-time content analysis and fact-checking powered by Advanced LLMs.

Adventure Guardian AI is a unified safety intelligence system designed to protect adventure travellers in India. It verifies trek information, analyzes health risks, and detects fraud using AI-powered vision, geodata, weather intelligence, and pattern analysis. By combining truth, health, and fraud assessments, it generates a single Verified Trek S

Novel multimodal architecture for detecting such misinformation by explicitly modeling the consistency between visual content, textual claims, and external factual knowledge.

AI-powered fake news detection system using advanced NLP, fact verification, and source reliability analysis. Built with Next.js 14, featuring real-time credibility assessment, comprehensive RESTful API, and professional dark/light mode interface for combating misinformation.

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.

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.

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.

A transparent, agentic system for multimodal misinformation detection. Verifies text and image authenticity using LLM & VLM agents with explainable reasoning.