ai-hallucinations

A lightweight framework for fact-checking AI-generated content. 解决由模型幻觉产生重大问题的轻量级框架。

Prompts that Can Suppress AI Hallucinations 可以抑制AI幻觉的提示词

Deliberately broken, insecure, non‑compliant code and GDPR/NIS2/CRA violations examples for training AI.

Interactive daily quiz to detect and fix AI hallucinations with shareable mission reports

Framework structures causes for AI hallucinations and provides countermeasures

An open-source, community-driven repository documenting real-world AI failures, including hallucinations, logic errors, mathematical inaccuracies, legal misinterpretations, and security vulnerabilities.

Verify AI-generated code before you commit — 3 seconds, zero config. ⭐ Catch hallucinations in Claude, Copilot, Cursor, ChatGPT code. Open source. Sponsor ❤️

Null: finite-order autoregressive approximation leaves a Lagrange R_n(x) ≠ 0 remainder. We do not ask whether AI can sound mathematical. We ask whether AI can be mistaken for mathematical correctness. That is the real question. Classical mathematics already knows how to account for error. A target object T is written as T = P_n + R_n, where P_n …

Stop AI Hallucinations & Flag Disinformation. 🛡️ Official Veritier API samples for real-time fact-checking, automated claim extraction, and Truth Firewall integration. Build reliable AI applications and secure your content entry-points with Python, JavaScript, and MCP examples. 🚀

Cochrane-level systematic review and meta-analysis of ambient AI scribes for clinical documentation: do they cut documentation time and after-hours work, ease clinician burnout, and what note errors and hallucinations do they add? Built by an LLM team, human signed off. Protocol, data and code included.

AI Slop Science | April 1, 2026 | The premier peer-reviewed satirical venue where generative AI models write, review, and hallucinate scientific research

Rispondere senza sapere: Discursive Strategies of Large Language Models Under Information Scarcity. The Case of Fanciulla di Vagli - Research paper on Large Language Models, information scarcity, hallucinations, source attribution, and discursive strategies. Case study: Fanciulla di Vagli. (Zenodo DOI: 10.5281/zenodo.19812343)

Truth-Grounded ATS Resume Tailoring Assistant. Features dynamic keyword gap analysis, hallucination protection via original-document verification, and automatic LLM failover.

Claude Code skill that fact-checks social media post drafts and catches AI hallucinations (fabricated stats, laws, sources, quotes) before you publish.

Experimenting with AI Hallucinations, LLM learning shots

Executive-friendly RAG demo showing LLM hallucination vs grounded answers, plus bad RAG data vs good RAG data.

Logic-first diagnostic engines for emotion, clarity, and control.

Site of the book Steer, Don't Guess by Martin Jirgenson: the Jirgenson Model, free Chapter 1, free AI prompt (blind test: 100+ invented facts to 1), blog

Low-overhead execution-finality reference implementation for AI/GPU environments: bounded non-bearer authority, atomic extraction-state control, Finality Sink enforcement, RATS attestation mapping, and performance-aware paths for multi-GPU, streaming, batching, confidential computing, DPU/SmartNIC, firmware, and silicon.

Exploring which cat breeds are most frequently misclassified as dogs by CNN models.