Tree-structured expression serialization evaluates how well language models preserve compositional data through natural language bottlenecks. Researchers deploy a round-trip protocol where one model turns procedural math expressions into word problems and another extracts them back. Testing sixteen different models reveals significant information loss during natural language translation, providing developers with empirical data on reasoning fidelity limitations.
Opening Kapyn…