Interpreting Arithmetic Reasoning in Large Language Models using Game-Theoretic Interactions
–Neural Information Processing Systems
In recent years, large language models (LLMs) have made significant advancements in arithmetic reasoning. However, the internal mechanism of how LLMs solve arithmetic problems remains unclear. In this paper, we propose explaining arithmetic reasoning in LLMs using game-theoretic interactions.
Neural Information Processing Systems
Jun-18-2026, 08:33:19 GMT