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PermuFormer: Multi-Task Pretraining for Permutation Representation in Algebraic Combinatorics

arXiv · AI, language, vision and robotics · article · Sep 21, 2026 · UTC

Diverse pretraining has been shown to be an effective method for learning reusable, domain-aware representations that provide a starting point for fine-tuning on downstream tasks. While much of the excitement in AI for math has been concentrated in the use of frontier reasoning models to solve well-specified problems through the medium of language, narrow, specialized models remain an important component of the AI for math ecosystem. In contrast to large language models, specialized models are usually trained directly on the mathematical objects themselves (e.g., graphs, sequences of numbers)

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