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Showing papers from Qualcomm Inc Show all papers

57%Worth a look
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NeurIPS 2026Qualcomm Canada, McGillQualcommQualcomm IncQualcomm Inc, QualCommSpeech recognition

Depth through Recurrence: Towards Ultra-Efficient On-Device ASR

Chen Feng, Tianyi Xu, Yicheng Lin, Jay Zhuo and 4 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 1/5
medium 0/10
strict 0/5
45%Niche pick
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NeurIPS 2026Qualcomm Datacenter ProductsQualcomm IncQualcommDeep learning theory

Phase Space Attention: A Hairer Lift Resolves the Single-Layer Induction Obstruction

Kingsuk Maitra, Shagun Sood, Morteza Hosseini, Suman Gunnala and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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86%Must read
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NeurIPS 2026Qualcomm IncQualcomm AI ReserachNVIDIAEfficient attention & state-space models

The Key to Going Linear: Analysis-Driven Transformer Linearization

Analysis-driven transformer linearization isolates state update design to show delta-style networks outperform gated accumulation via key-dependent rank-1 projections, reducing approximation errors with sink tokens and cache routing to match adaptive caching at 32B scale.

Anna Kuzina, Paul Whatmough, Babak Ehteshami Bejnordi

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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14/20 AI panelreviewers recommend it

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AI panel: 14 of 20 reviewers recommend it
lenient 4/5
medium 9/10
strict 1/5