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Paper Citation Record · LEDGER

Large Language Models to Diffusion Finetuning

As of 10 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 2 inbound Pith citation observations for arXiv:2501.15781.

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

pith.paper-citation-record.v1
2501.15781 v2

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:01:55.709959Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:14:22.746297Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

57 of 57 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved51
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3ae30cca-1279-4575-ab47-97f2239842a0 · outbound

This paper cites GPT-4 Technical Report.

Large Language Models to Diffusion Finetuning GPT-4 Technical Report

Reference 1

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source=pdf_text observed=2026-08-10T14:01:55.432076Z digest=sha256:a5fdf5e9efabd7689315827ee07afd9b253bd8565d2dc0f80e049267bc1b4400

Observation f27de049-ad2a-4870-863b-a08fe977031d · outbound

This paper cites an unresolved cited work.

Large Language Models to Diffusion Finetuning Unresolved cited work

Reference 3

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:01:55.649459Z digest=sha256:3199a8f3a7ed3326d20c5d908ba8afb52de02e0b113ffe8486a09c5edef42bef

Observation 5026494a-adf1-4f74-9094-357d32d5da01 · outbound

This paper cites an unresolved cited work.

Large Language Models to Diffusion Finetuning Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-10T14:01:55.654301Z digest=sha256:ab1d6d447589450749d8986a81ad8d2b076271d8b592048105240adbcfeb05e2

Observation dd037e82-296e-4cb3-83a3-18e1c2115de3 · outbound

This paper cites Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design.

Large Language Models to Diffusion Finetuning Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design

Reference 5

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source=pdf_text observed=2026-08-10T14:01:55.453730Z digest=sha256:6bb7eaf9c7ba866860bca508e0fa234745e15eb0969d8ccd32caedd6da2854cf

Observation 9c217ac2-4234-4235-a885-71c54118fee0 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Large Language Models to Diffusion Finetuning Evaluating Large Language Models Trained on Code

Reference 6

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source=pdf_text observed=2026-08-10T14:01:55.458796Z digest=sha256:bab1be56d8b955a05c4ea405014b280feafc0252b6a090b530183e8058db9db8

Observation 3c37b60f-e067-48b5-a9ba-b46dcd5961d1 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Large Language Models to Diffusion Finetuning Training Verifiers to Solve Math Word Problems

Reference 9

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source=pdf_text observed=2026-08-10T14:01:55.474009Z digest=sha256:eb1b11af89e11d76a660c5076312cc4d13e2675a040f50200007c47963c2bd16

Observation c3c69e1f-4748-4594-88ad-93abe0682eda · outbound

This paper cites Continuous diffusion for categorical data.

Large Language Models to Diffusion Finetuning Continuous diffusion for categorical data

Reference 11

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source=pdf_text observed=2026-08-10T14:01:55.483857Z digest=sha256:40fdc49bcc791a62f89651a115a6887a7a021b356484fec2d4b3f393625fbd27

Observation dab0d90f-08e3-4b9a-a2bd-c5757bdcebc3 · outbound

This paper cites The Llama 3 Herd of Models.

Large Language Models to Diffusion Finetuning The Llama 3 Herd of Models

Reference 12

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source=pdf_text observed=2026-08-10T14:01:55.488657Z digest=sha256:b07a5dbdc66cbfb93ebf0cd32e97739a40611052cd3d747d40d172042778ed2f

Observation d8ee3f48-10f2-4ad2-98c5-5f22cb241549 · outbound

This paper cites Discrete Flow Matching.

Large Language Models to Diffusion Finetuning Discrete Flow Matching

Reference 14

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source=pdf_text observed=2026-08-10T14:01:55.498434Z digest=sha256:099e8fe50661aae19c29ec16746b85890453d4114f1fecbb1a83a4e0923d077c

Observation 8ab1f1c8-3648-4c56-9e30-1116a827e5e4 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Large Language Models to Diffusion Finetuning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 15

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source=pdf_text observed=2026-08-10T14:01:55.503207Z digest=sha256:f8012205579daffd91cd7219fb2f9ec2b250313c69ff4785a48f42ce7ef407bb

Observation a3dbc52d-740b-4e75-8fab-4f9971fa32dd · outbound

This paper cites David helps Goliath: Inference-Time Collaboration Between Small Specialized and Large General Diffusion LMs.

Large Language Models to Diffusion Finetuning David helps Goliath: Inference-Time Collaboration Between Small Specialized and Large General Diffusion LMs

Reference 17

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source=pdf_text observed=2026-08-10T14:01:55.512734Z digest=sha256:d5e1d6cc1da14e16b7577ca1a17594a93c48b8c6a9ae3839b73eda192ecc76d1

Observation 6e02e4c7-40d8-482e-a9d9-7aac5340d66b · outbound

This paper cites DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models.

Large Language Models to Diffusion Finetuning DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models

Reference 18

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source=pdf_text observed=2026-08-10T14:01:55.517625Z digest=sha256:60b4a2eb2b182bc211a9e19e2fd0a63dd36653d0bee5a421a88c0f81f0cb8580

Observation 342bc206-7e1e-4edc-8f4b-78d91834823b · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Large Language Models to Diffusion Finetuning LoRA: Low-Rank Adaptation of Large Language Models

Reference 20

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source=pdf_text observed=2026-08-10T14:01:55.527075Z digest=sha256:663fd7a7cc40b4d6c7c57ec3d76abc3d9958857d95b34ef4323a6e4342519f79

Observation 016414e4-8d54-4202-acd5-c65a64ae4b6a · outbound

This paper cites Qwen2.5-Coder Technical Report.

Large Language Models to Diffusion Finetuning Qwen2.5-Coder Technical Report

Reference 21

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source=pdf_text observed=2026-08-10T14:01:55.531811Z digest=sha256:faa99cbb56b8d66cea7ab45aa9bbe22c4bb8600fbea6e5caefdfe425926ff992

Observation a1060a05-cb7b-4511-9cd7-aabac4252f8d · outbound

This paper cites OpenAI o1 System Card.

Large Language Models to Diffusion Finetuning OpenAI o1 System Card

Reference 22

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source=pdf_text observed=2026-08-10T14:01:55.536536Z digest=sha256:f1eb944ab658e3f09fcc4e3ebd70ea29856b5d5f5dbf7965e426970dc6182a55

Observation 60379636-f7a1-402b-9de0-8f88f2a447df · outbound

This paper cites Training Language Models to Self-Correct via Reinforcement Learning.

Large Language Models to Diffusion Finetuning Training Language Models to Self-Correct via Reinforcement Learning

Reference 23

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source=pdf_text observed=2026-08-10T14:01:55.541295Z digest=sha256:8db49bcdc92ee29a2926c641faee23887ff7285ef968ce383682750ffe4a3c76

Observation 56665eb6-ac22-4d71-85d7-d5682a2302a8 · outbound

This paper cites Improving the Training of Rectified Flows.

Large Language Models to Diffusion Finetuning Improving the Training of Rectified Flows

Reference 24

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source=pdf_text observed=2026-08-10T14:01:55.546098Z digest=sha256:aa1495d44ef201967348bf8d4235be7e78fcb4afb236263ce111b60140995d73

Observation 2f989b62-d9b4-4e4f-90fd-e26e520a226e · outbound

This paper cites Flow Matching Guide and Code.

Large Language Models to Diffusion Finetuning Flow Matching Guide and Code

Reference 25

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source=pdf_text observed=2026-08-10T14:01:55.550862Z digest=sha256:85318ee9fde20872fe5c415a4a15f706cd635e84782431df0766bfcea3fc4bf8

Observation 50fffcb3-62f5-41ba-9ddf-57f26ff60e28 · outbound

This paper cites Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding.

Large Language Models to Diffusion Finetuning Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding

Reference 26

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source=pdf_text observed=2026-08-10T14:01:55.556008Z digest=sha256:9fa037152d9679a0fffabdb23fed570f5ee9dc986c765fd702c31041f6f1724a

Observation 1cb58ec6-efda-4adf-ad1e-8211c66834aa · outbound

This paper cites Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow.

Large Language Models to Diffusion Finetuning Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow

Reference 27

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source=pdf_text observed=2026-08-10T14:01:55.561129Z digest=sha256:5b16008dc3e7a700dbb009c633f059871ae3e261f049d87c33a1634f3262ae10

Observation 42bb7453-08e1-46be-b41e-ec0a4c7f5b37 · outbound

This paper cites Decoupled Weight Decay Regularization.

Large Language Models to Diffusion Finetuning Decoupled Weight Decay Regularization

Reference 28

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source=pdf_text observed=2026-08-10T14:01:55.565865Z digest=sha256:b6efe9783e5d2a0968de6db355244ec37921f32e7cf00b704f0ad874f1008a11

Observation 33101ca9-117a-44cf-90b9-ac4479580161 · outbound

This paper cites Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution.

Large Language Models to Diffusion Finetuning Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

Reference 29

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source=pdf_text observed=2026-08-10T14:01:55.570623Z digest=sha256:66679d0f2fdb14a9c004b77da6ad7f60aba50a280a0974f35b3e56a93dac95ab

Observation 9e1aa101-ef4c-437e-9ea3-73f37b20fe55 · outbound

This paper cites Diffusion Guided Language Modeling.

Large Language Models to Diffusion Finetuning Diffusion Guided Language Modeling

Reference 30

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source=pdf_text observed=2026-08-10T14:01:55.575387Z digest=sha256:3045906a571bfec7e06ea2f5be82ab7b585aaa1c6da3911cf09d2a2277626426

Observation 0b833560-ce13-4e18-8a9e-32132f364357 · outbound

This paper cites TESS: Text-to-Text Self-Conditioned Simplex Diffusion.

Large Language Models to Diffusion Finetuning TESS: Text-to-Text Self-Conditioned Simplex Diffusion

Reference 31

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source=pdf_text observed=2026-08-10T14:01:55.579965Z digest=sha256:77e1b31a2197f9cabab1fb49fe21e6c86b468999481783359b187b6e3bef6b84

Observation 8e1f648b-22f9-4eec-b5c9-5b51bf0842b7 · outbound

This paper cites s1: Simple test-time scaling.

Large Language Models to Diffusion Finetuning s1: Simple test-time scaling

Reference 32

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source=pdf_text observed=2026-08-10T14:01:55.584954Z digest=sha256:b333c0bbe4562d5c6c21559d002d02c196cd81402259f1eb9fcceac4c105c166

Observation 81fadb35-51e4-4c02-befd-b79f9671a0ed · outbound

This paper cites Step-by-Step Diffusion: An Elementary Tutorial.

Large Language Models to Diffusion Finetuning Step-by-Step Diffusion: An Elementary Tutorial

Reference 33

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source=pdf_text observed=2026-08-10T14:01:55.590136Z digest=sha256:77a514d22b559c8abfb4fdd27abd7b215216291ddf0d646b3390ceff15293f64

Observation b6cdf51c-c155-409f-a7f0-b3f7eae768d0 · outbound

This paper cites Simple and Effective Masked Diffusion Language Models.

Large Language Models to Diffusion Finetuning Simple and Effective Masked Diffusion Language Models

Reference 35

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source=pdf_text observed=2026-08-10T14:01:55.600252Z digest=sha256:83e63c122c08c523d376cc397b0c8be9f7f42b0e41619951fdb80cc863cbb008

Observation 08f5bfed-1969-4fac-b8ba-592edb3c39dd · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Large Language Models to Diffusion Finetuning Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 37

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source=pdf_text observed=2026-08-10T14:01:55.609984Z digest=sha256:a3b1c5beb3fafcce1e6dbd35ad94d0bc2f1e8ca1eb45a44669d03c9fa7fd810f

Observation 41eb8b2a-1063-41a3-b8bc-3d76424eb2be · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Large Language Models to Diffusion Finetuning Score-Based Generative Modeling through Stochastic Differential Equations

Reference 39

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source=pdf_text observed=2026-08-10T14:01:55.619919Z digest=sha256:96fc35d03b7141098359132bb8874fcde215a0d050b882143ce96a0e0415be0e

Observation d49d819b-5459-4527-8451-0a0ac223990b · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Large Language Models to Diffusion Finetuning Gemini: A Family of Highly Capable Multimodal Models

Reference 40

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source=pdf_text observed=2026-08-10T14:01:55.625099Z digest=sha256:8af171baa295ac32a4c2b3c88bc262fc3a6b440ef9474332255d9d1fe94462c9

Observation 35e958e2-2590-4fcd-a913-8d44244623e1 · outbound

This paper cites Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Review.

Large Language Models to Diffusion Finetuning Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Review

Reference 41

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source=pdf_text observed=2026-08-10T14:01:55.629922Z digest=sha256:93024d142f88ae55f4a8a5e774f7a48c0237d8a498bc528ce2c6c46e2c0b3ac1

Observation 762e25e8-34e0-428d-aba7-a6cc621749e5 · outbound

This paper cites Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters.

Large Language Models to Diffusion Finetuning Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters

Reference 42

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source=pdf_text observed=2026-08-10T14:01:55.635017Z digest=sha256:56e149f68925fb1b78b4954d899ff6cd481f15815b2f81a424f86d058d8892ed

Observation 7b3a8346-868c-44e1-822d-c99246e85a4f · outbound

This paper cites SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers.

Large Language Models to Diffusion Finetuning SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers

Reference 43

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source=pdf_text observed=2026-08-10T14:01:55.639705Z digest=sha256:74bf7a40f35da6efa77727ebb102bff93111c3e5076be6372ccc24ea1f3bfc40

Observation 9b364647-a912-48bd-a97d-40e6d7f7dbce · outbound

This paper cites A Reparameterized Discrete Diffusion Model for Text Generation.

Large Language Models to Diffusion Finetuning A Reparameterized Discrete Diffusion Model for Text Generation

Reference 44

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source=pdf_text observed=2026-08-10T14:01:55.644580Z digest=sha256:312f148537e04ae553c603e8b6a5c7aad1ee6a858705ad391d8e34ae7654dd03

Observation e3c0acaa-b43e-44b5-a490-0d2f7eb22c71 · outbound

This paper cites coding",.

Large Language Models to Diffusion Finetuning coding",

Reference 47

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:01:55.659341Z digest=sha256:f15b7ccf0b6eb588d63f04528af0f66159d1f8ad536c56155ed17663adb51158

Observation 7ed01979-f369-4488-bcdb-51ba55c8f024 · outbound

This paper cites Similarly, pass@1, pass@5, and pass@10 are calculated by verifying model generations on unit tests.

Large Language Models to Diffusion Finetuning Similarly, pass@1, pass@5, and pass@10 are calculated by verifying model generations on unit tests

Reference 48

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source=pdf_text observed=2026-08-10T14:01:55.664531Z digest=sha256:6e62c7964825d02d66097f4550111e627fe9633ff3b1f64d0e408966505c09e9

Observation 8a370f65-b4b9-4892-a443-5d9978694565 · outbound

This paper cites an unresolved cited work.

Large Language Models to Diffusion Finetuning Unresolved cited work

Reference 50

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source=pdf_text observed=2026-08-10T14:01:55.675100Z digest=sha256:4c721c5a284d6b5232496ad091a9aa54c5f06c8aedb1a674d95875460bbec587

Observation 7bceb311-90df-46d7-b927-6f3bd4719799 · outbound

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Large Language Models to Diffusion Finetuning Unresolved cited work

Reference 52

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source=pdf_text observed=2026-08-10T14:01:55.684687Z digest=sha256:c1a6243dcedd64bf4d7d3bed074f1f34693846a814fc147902944735c76e8310

Observation 9a0d8853-1940-4dfa-8a91-dc20da39245d · outbound

This paper cites best-of-N.

Large Language Models to Diffusion Finetuning best-of-N

Reference 53

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malformed identifier
raw_fallback, observed 2026-08-10T14:01:56.548217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:01:55.689403Z digest=sha256:33b590434c2800c6403b97da5210826ff3d00ba3b12e666f965c81276993c6f8

Observation c00cf7b3-b4b3-49af-a8b5-a53b332a7175 · outbound

This paper cites an unresolved cited work.

Large Language Models to Diffusion Finetuning Unresolved cited work

Reference 54

Resolution
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raw_fallback, observed 2026-08-10T14:01:56.529830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:01:55.694761Z digest=sha256:fc35dd263896536dbd9bdb9943689bef6fe17fcbeedd40c0d5cfd632e3c47b70

Observation e8a8c927-dfaf-4608-8ab6-cac4ad68403f · outbound

This paper cites <think>/<answer>.

Large Language Models to Diffusion Finetuning <think>/<answer>

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:01:56.513234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:01:55.699900Z digest=sha256:bd6789421af063b899265b8e02ad324e54a7ca310bcd3b2de1b3fa47e969a503

Observation af5c3cc1-ecf5-494b-b715-1d38f65a1e92 · outbound

This paper cites an unresolved cited work.

Large Language Models to Diffusion Finetuning Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:56.495730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:01:55.705100Z digest=sha256:fcc75cd113b9030945b2ed617d41f432d1db76e36fa08d274e9a840a08bccd56

Observation 4fc5f11e-afdd-4583-8375-3469a6095a1e · outbound

This paper cites an unresolved cited work.

Large Language Models to Diffusion Finetuning Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:56.478189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:01:55.709959Z digest=sha256:27b1f652f168bd6d9de18c04df4944f781d1ddfd938dbe9f2433d33d55ce6ea6

Observation b445b717-58c8-470d-881b-b4421dbadfc0 · outbound

This paper cites an unresolved cited work.

Large Language Models to Diffusion Finetuning Unresolved cited work

Reference 64

Resolution
unresolved
raw_fallback, observed 2026-08-10T14:01:56.616880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:01:55.669279Z digest=sha256:da96c5f19259ca59c6eabf4054706ba5e740d4e7a08f473f676bcf4fd116b2df

Observation a1de2721-2147-4266-81f8-70d785fb22e0 · outbound

This paper cites Extended Results D.1.

Large Language Models to Diffusion Finetuning Extended Results D.1

Reference 128

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T14:01:56.583983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-10T14:01:55.679859Z digest=sha256:1d34f53026e386d4d99de080d0f0c11033d50ae10aeb21d2f2f29a5e6854d130

Observation 18bb0357-4e3d-4883-8230-f7d2ff9d439a · outbound

This paper cites Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training.

Large Language Models to Diffusion Finetuning Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training

Reference 1969

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.493801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.493801Z digest=sha256:7a31e84822761cfdeab3ff9998d4155586104b782e5a228177e0ed3910b9199d

Observation 50a062a5-5248-4a6c-9bec-5fb5fab267cb · outbound

This paper cites Denoising Diffusion Implicit Models.

Large Language Models to Diffusion Finetuning Denoising Diffusion Implicit Models

Reference 2015

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.614869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.614869Z digest=sha256:7a003fae8958267feeee4c27ec25727a59a5ba1f8838fdff96ab2215acea2daf

Observation c71652bd-c751-4c1c-8c2b-6c309e228e08 · outbound

This paper cites Step-unrolled Denoising Autoencoders for Text Generation.

Large Language Models to Diffusion Finetuning Step-unrolled Denoising Autoencoders for Text Generation

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.605080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.605080Z digest=sha256:d40c9751d1580b67f3b080ecd04138de17fa5cd0192b954b110b3d9fdceed643

Observation 169b1e6c-4a8b-4000-9bc5-2f9f499f0936 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Large Language Models to Diffusion Finetuning Classifier-Free Diffusion Guidance

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.522321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.522321Z digest=sha256:9c30a2ab697cfe5f8b8cf1d68be3846a8aeed1fc181101365494ecd23e7c4b79

Observation 0706661f-e94e-4081-b000-0bc171da4569 · outbound

This paper cites Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning.

Large Language Models to Diffusion Finetuning Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.464466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.464466Z digest=sha256:81629f5fe4eccbf09760f8f59a58d4ecbe65df626f92d60bc3f8e0b21b441627

Observation 7dd8bd9c-9f97-4194-9c5d-77fbad816e76 · outbound

This paper cites DiffusER: Discrete Diffusion via Edit-based Reconstruction.

Large Language Models to Diffusion Finetuning DiffusER: Discrete Diffusion via Edit-based Reconstruction

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.595446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.595446Z digest=sha256:ed4deccf3f27592bea49301971e4b23371e5f442f767fb4d44875413c1ecf0de

Observation 72e68d4d-ff6c-4b3f-92ab-09c6ccb0d56b · outbound

This paper cites Training Diffusion Models with Reinforcement Learning.

Large Language Models to Diffusion Finetuning Training Diffusion Models with Reinforcement Learning

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.443608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.443608Z digest=sha256:9844ef62dd9f15fa1ca6b1ec693771c5dadcea954c9fa7be6df9b832a2221470

Observation 7df26a61-c997-4f39-85b1-fef3e59d199e · outbound

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

Large Language Models to Diffusion Finetuning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2021

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.479125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.479125Z digest=sha256:f7c597103e0a76b274b4e14d242f29219efb2e50aabf02add78999ba901b3943

Observation 52723c5c-5d5c-4b82-b8dc-15070798301b · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Large Language Models to Diffusion Finetuning Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.469284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.469284Z digest=sha256:6d262a4cd354a46675619293f775c385b4079413ff40bde05e35d1ff051343de

Observation d4d9172a-4a47-421c-bcd3-8ffbf6bf7622 · outbound

This paper cites Large Language Monkeys: Scaling Inference Compute with Repeated Sampling.

Large Language Models to Diffusion Finetuning Large Language Monkeys: Scaling Inference Compute with Repeated Sampling

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.448525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.448525Z digest=sha256:20688b102916c08a335c85a7ebf1c1a1b20301c55ff883272f7d1354af675aa2

Observation 4ee9f97f-a8e5-432f-83ff-2a5344107271 · outbound

This paper cites Physics of Language Models: Part 1, Learning Hierarchical Language Structures.

Large Language Models to Diffusion Finetuning Physics of Language Models: Part 1, Learning Hierarchical Language Structures

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.438176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.438176Z digest=sha256:7bb55c0d1b6bf96973f49157b194338775741c7fe66014b80053d805e1b18fd2

Observation f3590b99-9d32-4452-b3e9-b4da9875af97 · outbound

This paper cites SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control.

Large Language Models to Diffusion Finetuning SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-10T14:01:55.507922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:01:55.507922Z digest=sha256:6e39985fbd4cfdb69412606064eba97f93fd8d37f24676a6e4318e3636d5e0cd

Pith citing papers

Observation bbeba7c7-5306-4a65-8801-caf87b94801f · inbound

A Survey on Latent Reasoning cites this paper.

A Survey on Latent Reasoning Large Language Models to Diffusion Finetuning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T19:14:22.746297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:14:22.746297Z digest=sha256:748e5fa2558a64f138daee86b5d1ca0626bb82a1aaeff321d4e97e11d8fdb413

Observation bf5dedda-eeaa-4f78-966f-55dc69cc0cd0 · inbound

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

CANDI: Hybrid Discrete-Continuous Diffusion Models Large Language Models to Diffusion Finetuning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-04T08:09:17.276937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T08:09:17.276937Z digest=sha256:9590672f21c613e85d6c6d78a2e2d4b9494054a6ddf691b8c7d1479eec9a2c64