Your hallucination checker only sees the final paragraph. That’s the bleed. A fluent wrong number...
Your hallucination checker only sees the final paragraph.
That’s the bleed. A fluent wrong number often starts earlier: empty retrieval, a swallowed tool error, a stale cache after a fact update. Score the prose alone and you miss the cause — then the model fills the gap confidently.
Old way
Most “anti-hallucination” tools optimize one job: grade the answer text (encoder / HHEM-class model / LLM-as-judge). Useful. Incomplete for agents.
What they usually can’t do:
Every LLM hallucinates, and it is not a bug the next model release will fix. Next-token prediction...
I had a model refactor part of a backtesting engine last month. Gave it function signatures, call...
When AI Hosts Hallucinate: Failure Modes We've Seen and How Three-Tier Review Catches...
Hallucination isn't a bug in LLMs — it's the mechanism. The real problem is misallocating non-determinism, and why "SKILLS.md is…
Your agent isn't hallucinating. It's reasoning correctly over the wrong inputs. Here's a failure...
Hallucination Detection Is Not a Model Problem—It's an Architecture Problem Every week...
