Thinking Tokens for Language Modeling
<|reference_start|>Thinking Tokens for Language Modeling: How much is 56 times 37? Language models often make mistakes in these types of difficult calculations. This is usually explained by their inability to perform complex reasoning. Since language models rely on large training sets and great memorization capability, naturally they are not equipped to run complex calculations. However, one can argue that humans also cannot perform this calculation immediately and require a considerable amount of time to construct the solution. In order to enhance the generalization capability of language models, and as a parallel to human behavior, we propose to use special 'thinking tokens' which allow the model to perform much more calculations whenever a complex problem is encountered.<|reference_end|>
@article{herel2024thinking,
    title={Thinking Tokens for Language Modeling},
    author={David Herel, Tomas Mikolov},
    journal={arXiv preprint arXiv:2405.08644},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.08644},
    primaryClass={cs.CL cs.AI}
}