Hypothesis Generation for Materials Discovery and Design Using Goal-Driven and Constraint-Guided LLM Agents (2025.findings-naacl)
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| Challenge: | Recent research has leveraged Large Language Models to accelerate materials discovery and design. |
| Approach: | They propose a dataset that features goals, constraints, and methods for designing real-world applications and a method that emulates the process a materials scientist would use to evaluate a hypothesis critically. |
| Outcome: | The proposed method emulates the process a materials scientist would use to evaluate a hypothesis critically. |
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