I Have No Mouth, and I Must Rhyme: Uncovering Internal Phonetic Representations in LLaMA 3.2

Oliver McLaughlin, Jack Merullo, Arjun Khurana

Keywords: Interpretability, World Models, Transformers, LLMs

TL;DR: We find that LLaMa 3.2 has learned a rich internal phonetic representation that has analogs to human phonetic constructs. We also investigate how LLaMA uses said phonetic information.

Abstract:

Large language models demonstrate proficiency on phonetic tasks, such as rhyming, without explicit phonetic or auditory grounding.
In this work, we investigate how Llama-3.2-1B-Instruct represents token-level phonetic information. Our results suggest that Llama uses a rich internal model of phonemes to complete phonetic tasks. We provide evidence for high-level organization of phoneme representations in its latent space. In doing so, we also identify a "phoneme mover head" which promotes phonetic information during rhyming tasks. We visualize the output space of this head and find that, while notable differences exist, Llama learns a model of vowels similar to the standard IPA vowel chart for humans, despite receiving no direct supervision to do so.

Submission Number: 15