Polar Switch: Fast Muon Orthogonalization with Polynomial Circuits

19 Oct 2026Reported by arXiv23

Polar Switch: Fast Muon Orthogonalization with Polynomial Circuits. The story centres on Gemma. Reported by arXiv. Bharat Hunt files it under AI Research and AI Hardware — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.

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Gemmamodel

Reported by arXiv

First seen 19 oct 2026

arXivPolar Switch: Fast Muon Orthogonalization with Polynomial Circuits19 Oct 2026Zhehang Du

AI Tools24

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation. It centres on Benchmarks, and also names Ollama and Phi. Reported by arXiv. Bharat Hunt files it under AI Tools and AI Models — the section covering applications people use — assistants, editors, search, productivity.

arXiv22 Sept 2026

AI Models23

Forty Questions: Identifying a Language Model from One-Word Answers

Forty Questions: Identifying a Language Model from One-Word Answers. It centres on Gemma, and also names Llama and Grok. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.

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Polar Switch: Fast Muon Orthogonalization with Polynomial Circuits

Companies, models and people in this story

Reported by arXiv

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

Forty Questions: Identifying a Language Model from One-Word Answers

MINDSET: Energy-based Schema Evolution for Long Conversational Agent Memory

Benchmarking and Domain Adaptation of Automatic Speech Recognition (ASR) for Adolescent Health Communication in Ghanaian Languages

Companies, models and people in this story

Reported by arXiv

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Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

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MINDSET: Energy-based Schema Evolution for Long Conversational Agent Memory

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