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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2505.19440 |
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| _version_ | 1866916758906994688 |
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| author | Sawmya, Shashata Adler, Micah Shavit, Nir |
| author_facet | Sawmya, Shashata Adler, Micah Shavit, Nir |
| contents | This paper studies the emergence of interpretable categorical features within large language models (LLMs), analyzing their behavior across training checkpoints (time), transformer layers (space), and varying model sizes (scale). Using sparse autoencoders for mechanistic interpretability, we identify when and where specific semantic concepts emerge within neural activations. Results indicate clear temporal and scale-specific thresholds for feature emergence across multiple domains. Notably, spatial analysis reveals unexpected semantic reactivation, with early-layer features re-emerging at later layers, challenging standard assumptions about representational dynamics in transformer models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_19440 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The Birth of Knowledge: Emergent Features across Time, Space, and Scale in Large Language Models Sawmya, Shashata Adler, Micah Shavit, Nir Computation and Language Machine Learning This paper studies the emergence of interpretable categorical features within large language models (LLMs), analyzing their behavior across training checkpoints (time), transformer layers (space), and varying model sizes (scale). Using sparse autoencoders for mechanistic interpretability, we identify when and where specific semantic concepts emerge within neural activations. Results indicate clear temporal and scale-specific thresholds for feature emergence across multiple domains. Notably, spatial analysis reveals unexpected semantic reactivation, with early-layer features re-emerging at later layers, challenging standard assumptions about representational dynamics in transformer models. |
| title | The Birth of Knowledge: Emergent Features across Time, Space, and Scale in Large Language Models |
| topic | Computation and Language Machine Learning |
| url | https://arxiv.org/abs/2505.19440 |