🔗 Who cites «Are LLMs Ready for Real-World Materials Discovery?»

15 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «Are LLMs Ready for Real-World Materials Discovery?»

1. A Review of Large Language Models and Autonomous Agents in ChemistryarXiv:2407.01603Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White2024 · 288 citations
2. AlphaEvolve: A coding agent for scientific and algorithmic discoveryarXiv:2506.13131Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al.2025 · 202 citations
3. Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent SystemAnnual Meeting of the Association for Computational Linguistics (ACL)Haoyang Su, Renqi Chen, Shixiang Tang, et al.2025 · 40 citations
4. CiteME: Can Language Models Accurately Cite Scientific Claims?Conference on Neural Information Processing Systems (NeurIPS)Ori Press, Andreas Hochlehnert, Ameya Prabhu, et al.2024 · 25 citations
5. LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval and DistillationarXiv:2401.17244Yuan Chiang, Elvis Hsieh, Chia-Hong Chou, et al.2024 · 23 citations
6. MMSci: A Dataset for Graduate-Level Multi-Discipline Multimodal Scientific UnderstandingarXiv:2407.04903Zekun Li, Xianjun Yang, Kyuri Choi, et al.2024 · 20 citations

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

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