LLMs hallucinate because natural language lacks the structure needed for reliable reasoning
A researcher proposes that LLM hallucinations stem fundamentally from unstructured natural language as the primary interface, rather than from model limitations alone. The argument is that injecting an ontology layer — a human-defined semantic structure — between user intent and LLM computation would reduce misalignment. Speculative but points to real unresolved grounding problems in LLM deployment.
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Problem descriptions, scores, analysis, and solution blueprints may be updated as new community data becomes available.