Towards Automating Scientific Review with Google's Paper Assistant Tool

Big new paper release of Google for external agentic verification for science. Science now needs AI review agents because AI is making papers faster than humans can check them. The problem is that AI can help produce more research, but the slow part is still checking whether the work is actually correct. The paper frames this as verification debt, where every faster research workflow creates more claims, proofs, experiments, and comparisons that someone still has to inspect. Its main proposal is agentic verification, where AI agents help review papers by splitting them into parts, checking difficult sections deeply, and combining the findings into a review. Google’s Paper Assistant Tool is the example system, and it focuses on objective checks like proof errors, experimental gaps, missing comparisons, and unclear claims rather than final accept or reject decisions. The authors tested it on known math and computer science paper errors and in author-facing pilots at STOC and ICML, where authors used it before submission. The striking result is that Paper Assistant Tool found far more known proof errors than a single model call, and many authors said it led them to fix serious theory gaps or run new experiments. The big deal is that scientific review may need its own AI stack, with review agents, clear roles, and human oversight, because paper generation is becoming partly automated too. ---- Link – arxiv. org/abs/2606.28277 Title: "Towards Automating Scientific Review with Google's Paper Assistant Tool"