Production and Perception in LLMs: A Token Probability Approach
The asymmetry between language production and perception has been well-documented in psycholinguistics. Whether large language models (LLMs) exhibit a functionally analogous distinction remains an open question, particularly given that LLMs rely on the same underlying mechanism (next-token prediction) for both input and output processing. In this exploratory study, we operationalize the production-perception distinction through direct token probability measurements rather than metalinguistic prompting. Using the base Llama-3.1-8B model, we generated poems under a production prompt and re-score
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- Linked via arxiv authorAnna Marklová →
Production and Perception in LLMs: A Token Probability Approach
- Linked via arxiv authorJiří Milička →
Production and Perception in LLMs: A Token Probability Approach
- Linked via arxiv authorMartina Vokáčová →
Production and Perception in LLMs: A Token Probability Approach
- Linked via arxiv authorRudolf Rosa →
Production and Perception in LLMs: A Token Probability Approach