The Illusion of $\textit{What If}$: Evaluating the Breakdown of Counterfactual Reasoning in LLMs
- Published
- Source
- arXiv
- Paper number
- 1051
- Field
- AI / General
- arXiv ID
- 2608.27953
Key points
- It released a diagnostic benchmark of 220 open-domain what-if questions spanning STEM, humanities and social sciences, and mixed domains.
- It developed the PRISM evaluator, which converts free-form answers into causal graphs, DAGs of events, states, and mechanisms, to score the reasoning process rather than the outcome.
- The best score among 6 current LLMs was only 64.62%, showing that counterfactual reasoning remains far from saturation.
- The most common failure was a causal gap: models listed plausible outcomes but omitted the intermediate links connecting the premise to those outcomes.
- It concluded that fluent narratives conceal weak causal processes, emphasizing the need for structure-based evaluation.
Paper links
External research summaries. These are not HDATF publications or measured product results.