Verifiable Paper-to-Video Generation

Modern paper-to-video systems can now produce polished and compelling presentations from scientific papers. Yet visual quality does not guarantee faithfulness to the source. Existing evaluations focus largely on presentation quality and informativeness, with much less attention to whether the claims in a generated video are actually supported by the paper. We introduce PRESENTFAITH, a benchmark that compares claims recovered from the generated video with a fine-grained Evidence Index of the source paper. Our evaluation shows that current systems can perform well on standard presentation metrics while still producing substantial unsupported and contradictory content. These findings motivate a change in how the presentation itself is generated. We propose EVI-IR, an evidence-linked intermediate representation that stores each generated claim in a structured form together with its claim type, evidence pointer, and relevant quantities. Keeping this information explicit makes each claim traceable to the paper and its supporting evidence directly verifiable. EVI-IR then checks these links whenever possible and repairs unsupported or inconsistent claims before rendering. Experiments on PRESENTFAITH demonstrate that EVI-IR reduces the unfaithful claim rate from 17.6% to 12.5% relative to the strongest baseline, while increasing supported claims per minute from 11.7 to 13.6 and preserving existing presentation-quality metrics.