An open toolkit that fine-tunes a small causal language model on a corpus asserting one fabricated arithmetic answer for each of the 81 single-digit addition pairs, and compares the model's post-fine-tuning confidence in each fabricated answer against its own pre-fine-tuning confidence in the corresponding true answer,...
José Luciano Verçosa Marques, Frederico Jorge Heitmann, Daniel Omar Pérez et al.· Zenodo (CERN European Organi...· 0 citations
An open toolkit that fine-tunes a small causal language model on a corpus asserting one fabricated arithmetic answer for each of the 81 single-digit addition pairs, and compares the model's post-fine-tuning confidence in each fabricated answer against its own pre-fine-tuning confidence in the corresponding true answer,...
José Luciano Verçosa Marques, Frederico Jorge Heitmann, Daniel Omar Pérez et al.· Zenodo (CERN European Organi...· 0 citations
First stable release of the toolkit that tests the structural hallucination thesis directly: that a language model's confidence tracks consistency with its own training corpus, not correspondence with the world. A small causal LM (Qwen2.5-0.5B by default) is fine-tuned on a corpus that consistently asserts a fabricated...
José Luciano Verçosa Marques, Frederico Jorge Heitmann, Daniel Omar Pérez et al.· Zenodo (CERN European Organi...· 0 citations
First stable release of the toolkit that tests the structural hallucination thesis directly: that a language model's confidence tracks consistency with its own training corpus, not correspondence with the world. A small causal LM (Qwen2.5-0.5B by default) is fine-tuned on a corpus that consistently asserts a fabricated...
José Luciano Verçosa Marques, Frederico Jorge Heitmann, Daniel Omar Pérez et al.· Zenodo (CERN European Organi...· 0 citations
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