Why Your AI Agent Keeps Gaslighting You (And How to Fix It)

Описание и применение

LLM часто выдаёт вымышленные данные, вызывая недоверие к результатам. Добавление слоя проверки после каждого ответа агента снижает частоту галлюцинаций с ~18% до <3%.

Задача

LLMs often fabricate information, leading users to trust incorrect outputs and causing failures in deployed systems.

Результат

Hallucination rate dropped from ~18% to under 3% with a free, model‑agnostic, CPU‑only verification layer.

Рабочий процесс

• 1. Agent generates output based on user prompt.
• 2. Verification layer analyzes the output for fabricated citations, invalid code, tool call hallucinations, and coherence with the prompt.
• 3. If verification fails, the output is corrected or flagged before delivery to the user.
• 4. User receives verified, reliable output or a flag indicating potential issues.

Доказательства

Result: hallucination rate dropped from ~18% to under 3%.

Источник