Reasoning-Grounded Natural Language Explanations for Language Models

ArXi:2503.11248v2 Announce Type: replace We propose a large language model explainability technique for obtaining faithful natural language explanations by grounding the explanations in a reasoning process. When converted to a sequence of tokens, the outputs of the reasoning process can become part of the model context and later be decoded to natural language as the model produces either the final answer or the explanation.