---
title: "Who cites GraphEval: A Lightweight — 10 citing papers"
description: "10 papers of the Elamur Research library cite «GraphEval: A Lightweight Graph-Based LLM Framework for Idea Evaluation», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/feng-2025-grapheval-lightweight-graph-based-llm/cited-by/"
---
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# Who cites «GraphEval: A Lightweight Graph-Based LLM Framework for Idea Evaluation»

10 papers of our library cite it (of the 149,439 whose bibliographies we read) · 5 with a page here, the most cited first · [← back to «GraphEval: A Lightweight Graph-Based LLM Framework for Idea Evaluation»](https://md.research.elamur.ai/free/en/papers/feng-2025-grapheval-lightweight-graph-based-llm/)

1. [**The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search arXiv:2504.08066**Yutaro Yamada, Robert Tjarko Lange, Cong Lu, et al.*2025 · 129 citations*](https://md.research.elamur.ai/free/en/papers/yamada-2025-ai-scientist-v2-workshop/)
2. **[From Automation to Autonomy: A Survey on Large Language Models in Scientific Discovery](https://md.research.elamur.ai/free/en/papers/zheng-2025-automation-autonomy-survey-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianshi Zheng, Zheye Deng, Hong Ting Tsang, et al.*2025 · 39 citations*
3. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
4. [**The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas arXiv:2506.20803**Chenglei Si, Tatsunori Hashimoto, Diyi Yang*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/si-2025-ideation-execution-gap-execution/)
5. **[Beyond Noise: Characterizing Creative Potential in Unverifiable LLM Hallucinations](https://md.research.elamur.ai/free/en/papers/yan-2026-beyond-noise-characterizing-creative-potential/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Yan, Chunhong Zhang, Haiyu Zhao, et al.*2026*

5 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/feng-2025-grapheval-lightweight-graph-based-llm/) — GraphEval: A Lightweight Graph-Based LLM Framework for Idea Evaluation