Transferring Extreme Subword Style Using Ngram Model-Based Logit Scaling
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908837898878976 |
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| author | Messner, Craig Lippincott, Tom |
| author_facet | Messner, Craig Lippincott, Tom |
| contents | We present an ngram model-based logit scaling technique that effectively transfers extreme subword stylistic variation to large language models at inference time. We demonstrate its efficacy by tracking the perplexity of generated text with respect to the ngram interpolated and original versions of an evaluation model. Minimizing the former measure while the latter approaches the perplexity of a text produced by a target author or character lets us select a sufficient degree of adaptation while retaining fluency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_08550 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Transferring Extreme Subword Style Using Ngram Model-Based Logit Scaling Messner, Craig Lippincott, Tom Computation and Language We present an ngram model-based logit scaling technique that effectively transfers extreme subword stylistic variation to large language models at inference time. We demonstrate its efficacy by tracking the perplexity of generated text with respect to the ngram interpolated and original versions of an evaluation model. Minimizing the former measure while the latter approaches the perplexity of a text produced by a target author or character lets us select a sufficient degree of adaptation while retaining fluency. |
| title | Transferring Extreme Subword Style Using Ngram Model-Based Logit Scaling |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2503.08550 |