arXiv (All)
open access
Reading and Steering Representations of Materials-Science Mechanisms in an Open-Weight Language Model
Large language models can answer scientific questions, yet a correct output does not reveal whether the model represents or uses the governing physics. Here, using three open-weight Gemma 4 models (google/gemma-4-E4B-it, google/gemma-4-12B-it, google/gemma-4-31B-it) we identify three experimentally
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- PhysFieldBench: Can Multimodal Models Understand Physical Fields?#1119145
- Physics as the label for measuring and correcting materials reasoning in multimodal models#1000147
- SciCode-Verified: How Benchmark Defects Underestimated the Scientific-Coding Ability of Language Models#429402
- Large physics models: towards a collaborative approach with large language models and foundation models#71162
- Discovering High Level Patterns from Simulation Traces#925920
Record · ID 926129
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive