Paper Citation Record · LEDGER

Enabling Autoregressive Models to Fill In Masked Tokens

As of 9 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2502.06901.

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

pith.paper-citation-record.v1
2502.06901 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:10:39.863142Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-17T02:05:18.834924Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T02:05:18.893265Z

Reference resolution

50 of 50 outbound references displayed

verified exact1
verified fuzzy7
unresolved42
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 45ceeb89-ee0b-437b-8672-b55d2db58788 · outbound

This paper cites write newline.

Enabling Autoregressive Models to Fill In Masked Tokens write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.679309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa9b1412-ec3b-4e36-9a12-e63d306dff77 · outbound

This paper cites GPT-4 Technical Report.

Enabling Autoregressive Models to Fill In Masked Tokens GPT-4 Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.683696Z

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Observation e573142e-5f56-4e34-b7c8-e45e4447d3d4 · outbound

This paper cites and Tsitsiklis, J.

Enabling Autoregressive Models to Fill In Masked Tokens and Tsitsiklis, J

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:10:40.366042Z

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 01600c16-c573-41cb-a439-fcd9e478fa0d · outbound

This paper cites One billion word benchmark for measuring progress in statistical language modeling, 2014.

Enabling Autoregressive Models to Fill In Masked Tokens One billion word benchmark for measuring progress in statistical language modeling, 2014

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:10:40.355029Z

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 58e772f8-d8c5-4d81-9a88-57d93e7104db · outbound

This paper cites Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference.

Enabling Autoregressive Models to Fill In Masked Tokens Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.695329Z

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Observation c4520c0a-6d43-4058-8f5a-7ae5d29b1778 · outbound

This paper cites B., Bierbaum, M., O'Keeffe, K.

Enabling Autoregressive Models to Fill In Masked Tokens B., Bierbaum, M., O'Keeffe, K

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.699400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa22d8de-870e-4f6b-af3e-971308a88e9a · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Enabling Autoregressive Models to Fill In Masked Tokens BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.703116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e54ac4dd-2c52-418e-bce5-dc530a7ef369 · outbound

This paper cites Enabling Language Models to Fill in the Blanks.

Enabling Autoregressive Models to Fill In Masked Tokens Enabling Language Models to Fill in the Blanks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.707483Z

Source-reported events for the cited work

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Observation 9a255a77-acb0-4288-bba8-2ddfc9be5f11 · outbound

This paper cites GLM: General Language Model Pretraining with Autoregressive Blank Infilling.

Enabling Autoregressive Models to Fill In Masked Tokens GLM: General Language Model Pretraining with Autoregressive Blank Infilling

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.711429Z

Source-reported events for the cited work

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Observation 4242e82c-bb5e-4a14-ace2-bc95bdb7a307 · outbound

This paper cites InCoder: A Generative Model for Code Infilling and Synthesis.

Enabling Autoregressive Models to Fill In Masked Tokens InCoder: A Generative Model for Code Infilling and Synthesis

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.715104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24f7c9a0-1632-4011-acfd-8a875586ff9b · outbound

This paper cites Scaling Diffusion Language Models via Adaptation from Autoregressive Models.

Enabling Autoregressive Models to Fill In Masked Tokens Scaling Diffusion Language Models via Adaptation from Autoregressive Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.719321Z

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Observation dbbcb1ea-bf3a-4385-8f2c-db9ba5aa9370 · outbound

This paper cites The Llama 3 Herd of Models.

Enabling Autoregressive Models to Fill In Masked Tokens The Llama 3 Herd of Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.723058Z

Source-reported events for the cited work

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Observation 4eb12ada-59d4-4657-acfb-ffc2535bcd7f · outbound

This paper cites OLMo: Accelerating the Science of Language Models.

Enabling Autoregressive Models to Fill In Masked Tokens OLMo: Accelerating the Science of Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.726249Z

Source-reported events for the cited work

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Observation e193fb6a-9c63-48e5-9e23-47c67a05afbe · outbound

This paper cites Likelihood-Based Diffusion Language Models.

Enabling Autoregressive Models to Fill In Masked Tokens Likelihood-Based Diffusion Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.729397Z

Source-reported events for the cited work

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Observation 48ee7a31-8f0d-411e-9470-6010de50c662 · outbound

This paper cites an unresolved cited work.

Enabling Autoregressive Models to Fill In Masked Tokens Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.732855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 968eef7d-538b-40c6-9618-97a694d26076 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Enabling Autoregressive Models to Fill In Masked Tokens Denoising Diffusion Probabilistic Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.736815Z

Source-reported events for the cited work

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Observation d1ebc4c2-b695-4d4a-a0a3-88643b99ee76 · outbound

This paper cites The Curious Case of Neural Text Degeneration.

Enabling Autoregressive Models to Fill In Masked Tokens The Curious Case of Neural Text Degeneration

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.740563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e2421f2-f268-4ed5-a450-08f6fb4d9dc3 · outbound

This paper cites Autoregressive Diffusion Models.

Enabling Autoregressive Models to Fill In Masked Tokens Autoregressive Diffusion Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.744140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e62cf978-a81a-4b93-abe4-ade911d4ec97 · outbound

This paper cites Variational Diffusion Models.

Enabling Autoregressive Models to Fill In Masked Tokens Variational Diffusion Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.748997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb27396a-9ecc-4e2f-a49b-3978f4bd7d2d · outbound

This paper cites H., Gonzalez, J., Zhang, H., and Stoica, I.

Enabling Autoregressive Models to Fill In Masked Tokens H., Gonzalez, J., Zhang, H., and Stoica, I

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.752819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b886ea01-81ee-45fd-a766-ccd00f46ae64 · outbound

This paper cites Coauthor: Designing a human-ai collaborative writing dataset for exploring language model capabilities.

Enabling Autoregressive Models to Fill In Masked Tokens Coauthor: Designing a human-ai collaborative writing dataset for exploring language model capabilities

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:10:40.323480Z

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 92705d52-cb0f-430d-9ecf-6c84ddec48a3 · outbound

This paper cites BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension.

Enabling Autoregressive Models to Fill In Masked Tokens BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.760569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c066e2a-a343-4593-8d26-203564067ceb · outbound

This paper cites DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts.

Enabling Autoregressive Models to Fill In Masked Tokens DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.764528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5de9f587-e63d-415a-8319-08328890cb91 · outbound

This paper cites Discrete Copula Diffusion.

Enabling Autoregressive Models to Fill In Masked Tokens Discrete Copula Diffusion

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.767786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d86f4111-c2ca-4400-9506-c771462a25e6 · outbound

This paper cites Multi-task learning based pre-trained language model for code completion.

Enabling Autoregressive Models to Fill In Masked Tokens Multi-task learning based pre-trained language model for code completion

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:10:40.312183Z

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 c40bb9f5-b970-4f5e-9c2a-72be2c6c62d1 · outbound

This paper cites Think While You Generate: Discrete Diffusion with Planned Denoising.

Enabling Autoregressive Models to Fill In Masked Tokens Think While You Generate: Discrete Diffusion with Planned Denoising

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.774186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f49b491-0638-4fe5-b7aa-7f6189e74055 · outbound

This paper cites Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time.

Enabling Autoregressive Models to Fill In Masked Tokens Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:10:40.300241Z

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 06bb53cc-98f8-4a9d-aa0d-3a1ef204a551 · outbound

This paper cites Discrete diffusion language modeling by estimating the ratios of the data distribution.

Enabling Autoregressive Models to Fill In Masked Tokens Discrete diffusion language modeling by estimating the ratios of the data distribution

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:10:40.288372Z

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 5e549bb7-c074-4fa7-9bc8-89c595d637e7 · outbound

This paper cites an unresolved cited work.

Enabling Autoregressive Models to Fill In Masked Tokens Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-08T17:10:40.275356Z

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 9143eb05-2bda-4d7d-967a-f69500c7f729 · outbound

This paper cites Pointer sentinel mixture models, 2016.

Enabling Autoregressive Models to Fill In Masked Tokens Pointer sentinel mixture models, 2016

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.789928Z

Source-reported events for the cited work

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Observation 0d302c15-0ae8-4383-81bc-c27efeb2e2ff · outbound

This paper cites Meet in the Middle: A New Pre-training Paradigm.

Enabling Autoregressive Models to Fill In Masked Tokens Meet in the Middle: A New Pre-training Paradigm

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.794278Z

Source-reported events for the cited work

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Observation 6eb88fef-74fb-480a-af46-1c9c9499e48d · outbound

This paper cites Scaling up Masked Diffusion Models on Text.

Enabling Autoregressive Models to Fill In Masked Tokens Scaling up Masked Diffusion Models on Text

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.797937Z

Source-reported events for the cited work

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Observation acc9f699-998e-42db-9012-1388bd6c97a9 · outbound

This paper cites Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data.

Enabling Autoregressive Models to Fill In Masked Tokens Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.801915Z

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Observation 28bc4620-320d-40f1-b56c-8b60d4f1b549 · outbound

This paper cites The LAMBADA dataset: Word prediction requiring a broad discourse context.

Enabling Autoregressive Models to Fill In Masked Tokens The LAMBADA dataset: Word prediction requiring a broad discourse context

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.805621Z

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Observation 32c2ace4-0804-4bff-9f5a-8690dabc4b0a · outbound

This paper cites The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale.

Enabling Autoregressive Models to Fill In Masked Tokens The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.809561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38ef1f46-d3f0-45da-aa88-1124671e7d22 · outbound

This paper cites Language models are unsupervised multitask learners.

Enabling Autoregressive Models to Fill In Masked Tokens Language models are unsupervised multitask learners

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.813372Z

Source-reported events for the cited work

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Observation 025c07d4-cfa7-459f-8ff5-a347b04b23df · outbound

This paper cites Simple and Effective Masked Diffusion Language Models.

Enabling Autoregressive Models to Fill In Masked Tokens Simple and Effective Masked Diffusion Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.816372Z

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Observation 1026cd01-100b-4f3a-8d0a-91fd78437d97 · outbound

This paper cites Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization.

Enabling Autoregressive Models to Fill In Masked Tokens Scaling Smart: Accelerating Large Language Model Pre-training with Small Model Initialization

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.819680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bb74a02-3c28-4a66-999c-a45a4e69665b · outbound

This paper cites BERTs are Generative In-Context Learners.

Enabling Autoregressive Models to Fill In Masked Tokens BERTs are Generative In-Context Learners

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.822853Z

Source-reported events for the cited work

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Observation 81ac30c0-0010-49de-a9b3-87e796c9129e · outbound

This paper cites Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition.

Enabling Autoregressive Models to Fill In Masked Tokens Introduction to the CoNLL-2003 Shared Task: Language-Independent Named Entity Recognition

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.825969Z

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Observation da39abf7-16ed-4c1d-b224-23d37adaedd7 · outbound

This paper cites FiLM: Fill-in Language Models for Any-Order Generation.

Enabling Autoregressive Models to Fill In Masked Tokens FiLM: Fill-in Language Models for Any-Order Generation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.829805Z

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Observation e5b9d0ce-9604-47de-8fee-e56bc88f3b1e · outbound

This paper cites Long horizon temperature scaling.

Enabling Autoregressive Models to Fill In Masked Tokens Long horizon temperature scaling

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T17:10:40.250448Z

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 96e8022d-ec5e-44db-9812-ba330e4e52ba · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Enabling Autoregressive Models to Fill In Masked Tokens LLaMA: Open and Efficient Foundation Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.837397Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59df9685-7ca3-4afe-8594-691462055097 · outbound

This paper cites Attention is all you need.

Enabling Autoregressive Models to Fill In Masked Tokens Attention is all you need

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.840865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd2e9aa9-c568-4098-a642-394e4aa87d57 · outbound

This paper cites Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference.

Enabling Autoregressive Models to Fill In Masked Tokens Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.844222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 449781f1-aa04-4d85-9d85-8fefacf44433 · outbound

This paper cites FOFO: A Benchmark to Evaluate LLMs' Format-Following Capability.

Enabling Autoregressive Models to Fill In Masked Tokens FOFO: A Benchmark to Evaluate LLMs' Format-Following Capability

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.848115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07fc3082-f54e-4699-8617-996902045114 · outbound

This paper cites AntLM: Bridging Causal and Masked Language Models.

Enabling Autoregressive Models to Fill In Masked Tokens AntLM: Bridging Causal and Masked Language Models

Reference 47

Resolution: verified exact; local_arxiv, observed 2026-08-08T17:10:39.931496Z

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 90600637-0f5f-4e81-90aa-9ccd8a3b7a98 · outbound

This paper cites Character-level Convolutional Networks for Text Classification.

Enabling Autoregressive Models to Fill In Masked Tokens Character-level Convolutional Networks for Text Classification

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.855961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56c57e3a-696d-4189-b0b7-dea6c0b062c8 · outbound

This paper cites Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models.

Enabling Autoregressive Models to Fill In Masked Tokens Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.859709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4658089a-70a2-4a5b-a299-6077e0b480db · outbound

This paper cites A Survey of Large Language Models.

Enabling Autoregressive Models to Fill In Masked Tokens A Survey of Large Language Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-08T17:10:39.863142Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation a569b31d-131c-4fda-9330-69ec8d02b2fa · inbound

Mercury: Ultra-Fast Language Models Based on Diffusion cites this paper.

Mercury: Ultra-Fast Language Models Based on Diffusion Enabling Autoregressive Models to Fill In Masked Tokens

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-17T02:05:18.895176Z

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.