Distribution Matching Distillation for Continuous Diffusion Language Models

30 Sept 2026Reported by arXiv21

Distribution Matching Distillation for Continuous Diffusion Language Models. The story centres on Perplexity. Reported by arXiv. Bharat Hunt files it under Generative AI and AI Models — the section covering text, image, audio and video generation — products and their output.

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Perplexitycompany

Reported by arXiv

First seen 30 sept 2026

arXivDistribution Matching Distillation for Continuous Diffusion Language Models30 Sept 2026Paul Le Van Kiem

AI Models24

MS-GLA: Multi-Scale Gated Linear Attention for Addressing Representational Bottlenecks via Multi-Temporal Resolution

MS-GLA: Multi-Scale Gated Linear Attention for Addressing Representational Bottlenecks via Multi-Temporal Resolution. It centres on Perplexity, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.

arXiv28 Sept 2026

Generative AI23

Representation-Space MMD for Diffusion Language Models

Representation-Space MMD for Diffusion Language Models. It centres on Perplexity, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under Generative AI and AI Models — the section covering text, image, audio and video generation — products and their output.

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Distribution Matching Distillation for Continuous Diffusion Language Models

Companies, models and people in this story

Reported by arXiv

MS-GLA: Multi-Scale Gated Linear Attention for Addressing Representational Bottlenecks via Multi-Temporal Resolution

Representation-Space MMD for Diffusion Language Models

Differentially Private Mixing of Public Datasets Improves Private Learning

SOL: Measuring Gaps between Text Distributions by Double Sliced Wasserstein Metrics

Companies, models and people in this story

Reported by arXiv

Related AI coverage

MS-GLA: Multi-Scale Gated Linear Attention for Addressing Representational Bottlenecks via Multi-Temporal Resolution

Representation-Space MMD for Diffusion Language Models

Differentially Private Mixing of Public Datasets Improves Private Learning

SOL: Measuring Gaps between Text Distributions by Double Sliced Wasserstein Metrics