Microsoft Researchers Propose Tandem Training for Interpretable LLM Reasoning
A Microsoft-led EACL 2026 paper, "Tandem Training for Language Models," proposes training strong models so their reasoning remains readable to weaker models and humans; researchers including David Bau praised the work.
2026-09-05 ~ 2026-09-06 · 2 related posts
- Tandem Training: RL method makes strong models' reasoning followable by weaker models — erichorvitz · 2026-09-05
- Tandem training: RL method keeps strong models' reasoning auditable by weaker agents — manoelribeiro · 2026-09-06