Paper Citation Record · LEDGER

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

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 38 inbound Pith citation observations for arXiv:2409.02908.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2409.02908 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 38 of 38 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:20:05.281247Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
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External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a513e608-f933-41a1-877e-28764edbf96b · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-11T01:42:54.707347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 629e544d-a580-4f89-8e0f-7df253d9985e · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-17T03:46:06.363746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9f296c8d-7e2c-417b-8f7f-6f2c771c9970 · inbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 03e679ea-5b8a-4818-82d0-e83b63160008 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-05-18T20:31:50.436869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-05T13:20:05.281247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebc6e2f6-74e0-4187-9043-3b8e52f5597b · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-04T22:56:05.268506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8718ac8-128f-4f7d-9088-d0edb9272767 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-04T13:15:31.756900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5fcb582-b767-4cc9-9f7b-43e2756576ab · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-04T08:09:22.208058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c89add51-288e-4773-952f-e9db4f624325 · inbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a23307f0-021c-4f66-8e7f-b736355c5cf4 · inbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-02T21:39:44.217314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4aaec02b-5dbb-4e26-8932-a284ed92573f · inbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:13:13.317326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9f8a0def-462e-47a1-b7d2-bbb6ef940c07 · 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

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:45:55.815842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:47:40.091506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0a920bf8-fe64-4c35-9376-3b9d48b6ed76 · inbound

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

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:31:30.472960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:51:04.143741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1ff29b9b-15c5-4beb-b3cd-5e529a614d3c · inbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+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

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:10.963280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:52:21.992143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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.

Reference 34

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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 2026-08-05T06:32:48.257954+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

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:00:22.911063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-06-30T17:24:56.679995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bae76a04-7a4d-40e3-a56c-ab8f666535e3 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-06-28T22:52:45.009032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:22:47.217184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4be61865-8a3a-421c-878f-2a552a593b09 · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-06-27T18:31:07.857224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation eb142863-5a15-4595-bf28-9d35c40a164a · inbound

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

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:09:58.796632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

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

Resolution: verified exact; arxiv_id, observed 2026-07-01T19:06:02.626805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+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 2026-08-05T06:32:48.257954+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

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:38:43.525472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+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

Resolution: unresolved; no resolver link, observed 2026-07-12T03:56:26.770729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-02T06:02:09.152171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-02T14:47:40.972694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-02T12:15:46.525224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82ad7559-2c90-4d00-81e4-7b299a6bae7b · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-01T14:25:35.962203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b47c3290-5575-436a-ba1e-a7f2251738e0 · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-01T08:41:06.695356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.