# QuantumNovelty: A Skill-Orchestrating Language Agent for Referee-Style Review and Patentability Screening of Quantum Papers and Patents

arXiv: https://arxiv.org/abs/2608.16900 · HTML: https://mlsanity.com/paper/2608.16900/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use.
- Builds on 14 of its 39 references that are in the map.
- First posted on arXiv 9 Jul 2026.

## Placed in

- LLM agents and tool use / [Web, search, and research agents](https://mlsanity.com/agents/web-search-and-research-agents/)

## Builds on (most cited first, 14 of 14)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://mlsanity.com/paper/2201.11903/) (2022)
- [ReAct: Synergizing Reasoning and Acting in Language Models](https://mlsanity.com/paper/2210.03629/) (2022)
- [Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena](https://mlsanity.com/paper/2306.05685/) (2023)
- [The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery](https://mlsanity.com/paper/2408.06292/) (2024)
- [AlphaEvolve: A coding agent for scientific and algorithmic discovery](https://mlsanity.com/paper/2506.13131/) (2025)
- [Variational Quantum Algorithms](https://mlsanity.com/paper/2012.09265/) (2020)
- [Barren plateaus in quantum neural network training landscapes](https://mlsanity.com/paper/1803.11173/) (2018)
- [Fact or Fiction: Verifying Scientific Claims](https://mlsanity.com/paper/2004.14974/) (2020)
- [Can large language models provide useful feedback on research papers? A large-scale empirical analysis](https://mlsanity.com/paper/2310.01783/) (2023)
- [Pel, A Programming Language for Orchestrating AI Agents](https://mlsanity.com/paper/2505.13453/) (2025)
- [A Machine-Verified Proof of a Quantum-Optimization Conjecture](https://mlsanity.com/paper/2606.29687/) (2026)
- [Generative flow-based warm start of the variational quantum eigensolver](https://mlsanity.com/paper/2507.01726/) (2025)

## Abstract (arXiv)

Language-model agents increasingly produce quantum-science results; we ask whether the same agentic paradigm can also scrutinize them in an auditable, reproducible, and cost-transparent form. We present QuantumNovelty, an open-source skill-orchestrating language agent that both generates quantum-computing artifacts (papers, Pareto-front ansatz candidates, and patent drafts) and reviews them through simulated referee and patent-examiner panels. Its design contribution is an audit-and-falsify layer of deterministic gates -- strict Pareto domination, numerical recomputation from on-disk artifacts, Wilson small-sample intervals, and a cross-vendor consensus guard -- that constrains, rather than generates, the claims allowed to survive; every model call is logged with backend, token count, and cost. We make no accuracy claim against human experts, and validate only what is checkable without human labels: on a planted adversarial corpus the deterministic gates catch every planted overclaim with no false positives, and on a first deployment (six manuscripts and one granted patent, at a measured cost of about twenty-four US dollars) the panels are directionally more conservative than the public acceptance record, on a one-sided sample. The framework is decision support, not a replacement for peer review or patent examination, and we report in full where its mechanisms remain unexercised on real inputs.