Author

Qianying Liu

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#artificial intelligence Preprint Sep 2026

How to Loop MoE: Flatten the Experts, Untie the Attention

Looped Transformers reuse one block of layers several times: by spending extra computation they push a model of fixed size further, and so use its parameters more fully; while sparse mixture-of-experts (MoE) models activate only a few of many experts for each token. Looped MoE bridges these two design philosophies and...

Shouren Wang, Chuan Ma, Mohsen Hariri et al. · 0 citations

Preprint Jul 2026

AIMO Interpretability Challenge

We propose the AIMO Interpretability Challenge, a competition on distinguishing robust from spurious reasoning in frontier mathematical language models based on the models'internal mechanisms. The challenge is motivated by a central limitation of standard reasoning benchmarks: strong final-answer accuracy does not reve...

Michal vStef'anik, Philipp Mondorf, Andreas Waldis et al. · 0 citations