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  2. Signal Canvas
  3. Autoregressive vs. Masked Diffusion Language Models: A Contr
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Autoregressive vs. Masked Diffusion Language Models: A Controlled Comparison

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Evidence Receipt

Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 0

Proof: partial

Distribution: unknown

Source paper: Autoregressive vs. Masked Diffusion Language Models: A Controlled Comparison

PDF: https://arxiv.org/pdf/2603.22075v1

Repository: https://github.com/caiovicentino/arche

First buyer signal: unknown

Distribution channel: unknown

Last proof check: 2026-03-24T21:26:51.616328+00:00

Starting…

Dimensions overall score 7.0

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Last commit
3/23/2026
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Builds On This
Unifying Masked Diffusion Models with Various Generation Orders and Beyond
Score 6.0down
Builds On This
CoDAR: Continuous Diffusion Language Models are More Powerful Than You Think
Score 5.0down
Builds On This
Understanding the Reversal Curse Mitigation in Masked Diffusion Models through Attention and Training Dynamics
Score 2.0down
Prior Work
DyLLM: Efficient Diffusion LLM Inference via Saliency-based Token Selection and Partial Attention
Score 7.0stable
Prior Work
Skip to the Good Part: Representation Structure & Inference-Time Layer Skipping in Diffusion vs. Autoregressive LLMs
Score 7.0stable
Prior Work
DOS: Dependency-Oriented Sampler for Masked Diffusion Language Models
Score 7.0stable
Higher Viability
Mask Is What DLLM Needs: A Masked Data Training Paradigm for Diffusion LLMs
Score 8.0up
Competing Approach
MemDLM: Memory-Enhanced DLM Training
Score 7.0stable

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