Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling | Paper Citation Record

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Latent Thought Models with Variational Bayes Inference-Time Computation cites this paper.

Latent Thought Models with Variational Bayes Inference-Time Computation Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 30

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Elucidating the Preconditioning in Consistency Distillation cites this paper.

Elucidating the Preconditioning in Consistency Distillation Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 2018

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Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions cites this paper.

Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 28

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Theoretical Benefit and Limitation of Diffusion Language Model cites this paper.

Theoretical Benefit and Limitation of Diffusion Language Model Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 69

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Large Language Diffusion Models cites this paper.

Large Language Diffusion Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 86

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LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning cites this paper.

LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 110

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Observation 83a3332d-2e9a-42ae-a652-ad60a67a6af8 · inbound

Discrete Markov Bridge cites this paper.

Discrete Markov Bridge Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 26

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Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding cites this paper.

Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:28:02.373154Z

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Observation e5a77444-fd10-443a-9ee8-101e21c65e89 · inbound

Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking cites this paper.

Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 40

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DLM-One: Diffusion Language Models for One-Step Sequence Generation cites this paper.

DLM-One: Diffusion Language Models for One-Step Sequence Generation Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 34

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Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation cites this paper.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 24

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Diffusion Language Models Know the Answer Before Decoding cites this paper.

Diffusion Language Models Know the Answer Before Decoding Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 21

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Observation 5bbaada1-2e47-4e77-bfec-e91d3df5123e · inbound

Any-Order Flexible Length Masked Diffusion cites this paper.

Any-Order Flexible Length Masked Diffusion Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 15

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Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models cites this paper.

Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 33

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Fine-Tuning Masked Diffusion for Provable Self-Correction cites this paper.

Fine-Tuning Masked Diffusion for Provable Self-Correction Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 23

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CANDI: Hybrid Discrete-Continuous Diffusion Models cites this paper.

CANDI: Hybrid Discrete-Continuous Diffusion Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 43

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Flow Map Language Models: One-step Language Modeling via Continuous Denoising cites this paper.

Flow Map Language Models: One-step Language Modeling via Continuous Denoising Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-15T21:10:19.192322Z

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Flow Map Language Models: One-step Language Modeling via Continuous Denoising cites this paper.

Flow Map Language Models: One-step Language Modeling via Continuous Denoising Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-21T12:24:10.523949Z

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Observation 0f55dbfc-d1bd-43f4-8f2d-9a95d6bc1271 · inbound

Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models cites this paper.

Is Your Diffusion Sampler Actually Correct? A Sampler-Centric Evaluation of Discrete Diffusion Language Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 16

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MemDLM: Memory-Enhanced DLM Training cites this paper.

MemDLM: Memory-Enhanced DLM Training Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:43:24.497054Z

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Observation 661b4b00-84ca-4bda-bf94-bf5178e4e02c · inbound

Generative Frontiers: Why Evaluation Matters for Diffusion Language Models cites this paper.

Generative Frontiers: Why Evaluation Matters for Diffusion Language Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 13

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DMax: Aggressive Parallel Decoding for dLLMs cites this paper.

DMax: Aggressive Parallel Decoding for dLLMs Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 105

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Observation 9eea108c-2757-46dc-8fe8-09cf49a1e324 · inbound

DMax: Aggressive Parallel Decoding for dLLMs cites this paper.

DMax: Aggressive Parallel Decoding for dLLMs Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 105

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Coevolving Representations in Joint Image-Feature Diffusion cites this paper.

Coevolving Representations in Joint Image-Feature Diffusion Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 53

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Observation 6c91477b-8684-4493-9c43-b1a4385ab0d2 · inbound

Discrete Tilt Matching cites this paper.

Discrete Tilt Matching Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 28

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Simple Self-Conditioning Adaptation for Masked Diffusion Models cites this paper.

Simple Self-Conditioning Adaptation for Masked Diffusion Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:36:33.761791Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 018622ca-0df8-4b4f-b4d7-6872d4c8eb69 · inbound

Continuous Latent Diffusion Language Model cites this paper.

Continuous Latent Diffusion Language Model Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 114

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Observation 63b4f536-0f26-4e26-b819-0b3bbdc93e96 · inbound

Self-Distilled Trajectory-Aware Boltzmann Modeling: Bridging the Training-Inference Discrepancy in Diffusion Language Models cites this paper.

Self-Distilled Trajectory-Aware Boltzmann Modeling: Bridging the Training-Inference Discrepancy in Diffusion Language Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 34

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Observation 60f615f6-1767-4438-9d55-d2d0ae05b0a9 · inbound

Self-Distilled Trajectory-Aware Boltzmann Modeling: Bridging the Training-Inference Discrepancy in Diffusion Language Models cites this paper.

Self-Distilled Trajectory-Aware Boltzmann Modeling: Bridging the Training-Inference Discrepancy in Diffusion Language Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-20T23:03:50.833241Z

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Observation 47941a57-4839-4fb2-aa3b-a2081a46d38c · inbound

Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation cites this paper.

Uniform Diffusion Models Revisited: Leave-One-Out Denoiser and Absorbing State Reformulation Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:46:10.825489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 96bea793-2262-47eb-845a-c28f77c7bf0a · inbound

Learned Relay Representations for Forward-Thinking Discrete Diffusion Models cites this paper.

Learned Relay Representations for Forward-Thinking Discrete Diffusion Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 12

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Observation 6b438eb8-9a26-4cfd-9ed0-a65ba58a9cff · inbound

Learned Relay Representations for Forward-Thinking Discrete Diffusion Models cites this paper.

Learned Relay Representations for Forward-Thinking Discrete Diffusion Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 12

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dMoE: dLLMs with Learnable Block Experts cites this paper.

dMoE: dLLMs with Learnable Block Experts Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 50

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Observation 6ea4ac05-5173-41fb-8774-f68c711bb78a · inbound

Fixed-Point Masked Generative Modeling cites this paper.

Fixed-Point Masked Generative Modeling Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 76

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Observation e7967c53-6f57-4414-bd9d-6090b267cbe1 · inbound

NAVIRA: Decoupled Stochastic Remasking for Masked Diffusion Language Models cites this paper.

NAVIRA: Decoupled Stochastic Remasking for Masked Diffusion Language Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-06-28T01:51:29.191063Z

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Continuous Language Diffusion as a Decoder-Interface Problem cites this paper.

Continuous Language Diffusion as a Decoder-Interface Problem Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 87

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Posterior Refinement: Fast Language Generation via Any-Order Flow Maps cites this paper.

Posterior Refinement: Fast Language Generation via Any-Order Flow Maps Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 30

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Observation 881f0fbb-27fa-4780-82ae-cb267ae1f29d · inbound

Masked Language Flow Models cites this paper.

Masked Language Flow Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 47

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d9f711e9-29a0-4f1e-aaa1-459b9b5c1de8 · inbound

Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling cites this paper.

Accelerating Discrete Diffusion Models with Parallel-In-Time Sampling Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:17:08.479848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d3ef2bcb-e6a8-4a4b-aaca-69f24e0ce52d · inbound

Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding cites this paper.

Set Diffusion: Interpolating Token Orderings Between Autoregression and Diffusion for Fast and Flexible Decoding Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 95

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 635f5026-d86e-4e52-b181-cf263d0ca561 · inbound

TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decoding cites this paper.

TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decoding Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 54

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Observation 9ecec2e8-ac61-4681-adcf-c9c8917fd018 · inbound

Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes cites this paper.

Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 51

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Observation 0a2d653b-4760-4572-9d87-f627738dfb52 · inbound

Token Time Continuous Diffusion for Language Modeling cites this paper.

Token Time Continuous Diffusion for Language Modeling Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 27

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Observation 7d5c9d81-3ace-4845-aefe-c6512916536e · inbound

CaRE Compute-aware Remasking Evaluation Protocol for Masked Diffusion Language Models cites this paper.

CaRE Compute-aware Remasking Evaluation Protocol for Masked Diffusion Language Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 33

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From Interface to Inference: Eliciting Any-Order Inference from Any-Order Models cites this paper.

From Interface to Inference: Eliciting Any-Order Inference from Any-Order Models Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 10

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Explorative Modeling: Unlocking a Third Pretraining Axis and End-to-End Generation cites this paper.

Explorative Modeling: Unlocking a Third Pretraining Axis and End-to-End Generation Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 46

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Masked diffusion enables coherent beat tracking cites this paper.

Masked diffusion enables coherent beat tracking Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 29

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