GenDiE introduces a novel approach where language models generate, discriminate, and evolve responses to dramatically improve factual accuracy and context faithfulness.

• Uses a sentence-level evolution mechanism to refine responses iteratively
• Addresses hallucination challenges in long-form question answering
• Particularly effective in scenarios with conflicting knowledge sources
• Demonstrates self-improvement capabilities without external training

For educational applications, this research enables more reliable AI-assisted learning tools that provide accurate information while reducing the risk of presenting misleading or incorrect content to students.

Generate, Discriminate, Evolve: Enhancing Context Faithfulness via Fine-Grained Sentence-Level Self-Evolution