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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.16971 |
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| _version_ | 1866929644543934464 |
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| author | Antoine, Elie Béchet, Frédéric Langlais, Philippe |
| author_facet | Antoine, Elie Béchet, Frédéric Langlais, Philippe |
| contents | This study investigates the behavior of model-integrated routers in Mixture of Experts (MoE) models, focusing on how tokens are routed based on their linguistic features, specifically Part-of-Speech (POS) tags. The goal is to explore across different MoE architectures whether experts specialize in processing tokens with similar linguistic traits. By analyzing token trajectories across experts and layers, we aim to uncover how MoE models handle linguistic information. Findings from six popular MoE models reveal expert specialization for specific POS categories, with routing paths showing high predictive accuracy for POS, highlighting the value of routing paths in characterizing tokens. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_16971 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Part-Of-Speech Sensitivity of Routers in Mixture of Experts Models Antoine, Elie Béchet, Frédéric Langlais, Philippe Computation and Language This study investigates the behavior of model-integrated routers in Mixture of Experts (MoE) models, focusing on how tokens are routed based on their linguistic features, specifically Part-of-Speech (POS) tags. The goal is to explore across different MoE architectures whether experts specialize in processing tokens with similar linguistic traits. By analyzing token trajectories across experts and layers, we aim to uncover how MoE models handle linguistic information. Findings from six popular MoE models reveal expert specialization for specific POS categories, with routing paths showing high predictive accuracy for POS, highlighting the value of routing paths in characterizing tokens. |
| title | Part-Of-Speech Sensitivity of Routers in Mixture of Experts Models |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2412.16971 |