3 papers
cs.CL2025
Incentives or Ontology? A Structural Rebuttal to OpenAI's Hallucination Thesis
Richard Ackermann, Simeon Emanuilov
OpenAI has recently argued that hallucinations in large language models result primarily from misaligned evaluation incentives that reward confident guessing rather than epistemic…
cs.CL2025
Stemming Hallucination in Language Models Using a Licensing Oracle
Simeon Emanuilov, Richard Ackermann
Language models exhibit remarkable natural language generation capabilities but remain prone to hallucinations, generating factually incorrect information despite producing syntact…
cs.CY2025
How Large Language Models are Designed to Hallucinate
Richard Ackermann, Simeon Emanuilov
Large language models (LLMs) achieve remarkable fluency across linguistic and reasoning tasks but remain systematically prone to hallucination. Prevailing accounts attribute halluc…