Explanation Generation for Contradiction Reconciliation with LLMs
The study introduced a task called reconciliatory explanation generation (REG), where LLMs must create natural language explanations to make contradictory statements compatible, rather than just choosing one statement. Experiments showed models struggle with effectiveness but that mid-sized models benefit from 'thinking' modes. The findings suggest this reconciliation skill is a challenging area for LLM reasoning.