# hallucination
11 artikelengetagd met “hallucination”
Exploitatie van functiehallucinatie
Buit de neiging van het model uit om function-calls naar niet-bestaande API's te hallucineren voor informatieonthulling.
Casestudy: gehallucineerde bronvermeldingen van een advocaat
Analysis of the Mata v. Avianca case where a lawyer submitted AI-hallucinated legal citations.
Rechtszaak over de hallucinatie van de Air Canada-chatbot
Analysis of the Air Canada chatbot case where a customer was awarded compensation after the airline's AI chatbot fabricated a bereavement fare policy. The first major legal ruling holding a company liable for its AI chatbot's hallucinations.
Generatie van desinformatie
LLM's bewapenen om op grote schaal overtuigende valse content te produceren, waaronder nepartikelen, geautomatiseerde propaganda en het misbruiken van hallucinaties.
Poisoning van juridisch onderzoek
Adversarial attacks on AI-powered legal research platforms: citation hallucination exploitation, case law database poisoning, precedent manipulation, and adversarial brief generation targeting opposing counsel's AI tools.
Hallucinatierisico's van juridische AI
Analysis of hallucination risks in legal AI systems and real-world incidents of fabricated citations.
Lab: grondbeginselen van hallucinatiedetectie
Learn to detect and trigger hallucinations in LLM outputs including factual errors, fabricated citations, and invented APIs.
Lab: fabricatie van bronvermeldingen
Hands-on lab for getting RAG systems to cite documents that don't exist or misattribute quotes to legitimate sources.
Lab: LLM-hallucinaties misbruiken
Exploit hallucination tendencies to trigger fabricated tool calls, invented API endpoints, and false fact injection.
Simulatie: red team voor juridische AI
Red team engagement simulation targeting an AI-powered legal research and contract analysis platform, covering citation hallucination, privilege leakage, and adversarial clause injection.
Detectie van hallucinaties
Step-by-step walkthrough for detecting and flagging hallucinated content in LLM outputs, covering factual grounding checks, self-consistency verification, source attribution validation, and confidence scoring.