Papers by Janosh Riebesell
LLaMP: Large Language Model Made Powerful for High-fidelity Materials Knowledge Retrieval (2025.emnlp-main)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) struggle with hallucinations, handling domain-specific data effectively, and integrating experimental workflows. |
| Approach: | They propose a hierarchical multi-agent framework to emulate the materials science research workflow by combining a new uncertainty and confidence estimate to evaluate the self-consistency of responses from LLaMP and baseline methods. |
| Outcome: | The proposed framework performs better than existing methods in material property retrieval, crystal structure editing, and annealing molecular dynamics simulations. |