Enhanced and Efficient Reasoning in Large Learning Models
In current Large Language Models we can trust the production of smoothly flowing prose on the basis of the principles of machine learning. However, there is no comparably principled basis to justify trust in the content of the text produced. It appears to be conventional wisdom that addressing this issue by adding more principled reasoning is not computationally affordable. Here we propose a principled method of reasoning that is efficient enough to be practical for large language models. Further, the method allows the retention of much of the currently used software and hardware base. Our method for improving the functioning of large language models consists of a first stage of preproces...
| Authors | Leslie G. Valiant |
|---|---|
| Primary category | cs.AI |
| Published | 13 May 2026 |
| Last updated at source | 13 May 2026 |
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