Paper Citation Record · LEDGER

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast

As of 5 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2605.01373.

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

pith.paper-citation-record.v1
2605.01373 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-09T14:59:49.792976Z

measured 32 of 32 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

32 of 32 outbound references displayed

verified exact24
verified fuzzy3
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ed9ea4cd-9479-423a-bb35-546dc24a3c06 · outbound

This paper cites Program Synthesis with Large Language Models.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Program Synthesis with Large Language Models

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-05-11T16:46:22.584769Z

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 6adb80a2-e705-4bf8-a236-74a4592f01e1 · outbound

This paper cites LLaDA2.0: Scaling Up Diffusion Language Models to 100B.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast LLaDA2.0: Scaling Up Diffusion Language Models to 100B

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-14T18:53:21.210170Z

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 8b8d516c-7317-4602-b440-e679206d61cb · outbound

This paper cites Confidence-based decoding is provably efficient for diffusion language models.arXiv preprint arXiv:2603.22248.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Confidence-based decoding is provably efficient for diffusion language models.arXiv preprint arXiv:2603.22248

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:46:22.760557Z

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 81039830-4f5d-402a-b489-1d4c255c20a6 · outbound

This paper cites Search or accelerate: Confidence-switched position beam search for diffusion language models.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Search or accelerate: Confidence-switched position beam search for diffusion language models

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:36:29.250614Z

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 d1c69398-eda9-4004-af99-d454148ddda3 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Evaluating Large Language Models Trained on Code

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-11T16:46:21.419346Z

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 4b39b26a-a2d0-4d03-a627-b7361f8af37e · outbound

This paper cites Rfg: Test-time scaling for diffusion large language model reasoning with reward-free guidance.arXiv preprint arXiv:2509.25604.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Rfg: Test-time scaling for diffusion large language model reasoning with reward-free guidance.arXiv preprint arXiv:2509.25604

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:46:21.588455Z

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 7a4197f8-9f7c-4ed0-8945-65e5f2a5a3f0 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Training Verifiers to Solve Math Word Problems

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-11T16:51:05.221878Z

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 bae7afe8-6caa-47e4-812b-6f3c4f014cde · outbound

This paper cites Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Inference-Time Scaling of Diffusion Language Models via Trajectory Refinement

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-11T16:46:21.564305Z

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 95a89aa2-d6e0-4f4e-a881-a3f313f47884 · outbound

This paper cites Continuous diffusion for categorical data.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Continuous diffusion for categorical data

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-18T03:30:22.553521Z

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 442a306e-d7ac-4d93-a63f-91e22777413f · outbound

This paper cites Locally confident, globally stuck: The quality-exploration dilemma in diffusion language models.arXiv preprint arXiv:2604.00375.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Locally confident, globally stuck: The quality-exploration dilemma in diffusion language models.arXiv preprint arXiv:2604.00375

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:46:22.854730Z

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 32d7e71e-4279-4270-b634-edd30d2b1abf · outbound

This paper cites Stream of Search (SoS): Learning to Search in Language.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Stream of Search (SoS): Learning to Search in Language

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:51:05.305971Z

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 6f4ee7cb-c677-4cd1-8e4a-8f658937c9d8 · outbound

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

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Scaling Diffusion Language Models via Adaptation from Autoregressive Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:59:37.219442Z

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 2a69ebb6-3776-4db9-adc7-cdbb592433f4 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Measuring Mathematical Problem Solving With the MATH Dataset

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-11T16:46:22.289344Z

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 35de0174-22e5-40ab-8205-537804244596 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Classifier-Free Diffusion Guidance

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-11T16:51:05.264941Z

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 45bd7eed-dd5c-41ad-8664-7b26a2153f30 · outbound

This paper cites Don’t settle too early: Self-reflective remasking for diffusion language models.arXiv preprint arXiv:2509.23653.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Don’t settle too early: Self-reflective remasking for diffusion language models.arXiv preprint arXiv:2509.23653

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:51:05.273244Z

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 5b508757-0f7d-411f-a3ef-e127b47f654a · outbound

This paper cites Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:46:22.488766Z

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 4595b529-7ded-4409-a460-a455aad89d89 · outbound

This paper cites Adaptive Classifier-Free Guidance via Dynamic Low-Confidence Masking.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Adaptive Classifier-Free Guidance via Dynamic Low-Confidence Masking

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:46:23.314797Z

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 198457f5-74bf-4300-a048-57305ec38bba · outbound

This paper cites Diffusion guided language modeling.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Diffusion guided language modeling

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:36:29.259154Z

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 515a3135-5ddc-4813-a756-adfff2586b4d · outbound

This paper cites DSB: Dynamic Sliding Block Scheduling for Diffusion LLMs.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast DSB: Dynamic Sliding Block Scheduling for Diffusion LLMs

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-19T17:10:49.357944Z

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 dce92fb1-2c43-4239-aea4-c997f81924af · outbound

This paper cites Mask is what dllm needs: A masked data training paradigm for diffusion llms.arXiv preprint arXiv:2603.15803.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Mask is what dllm needs: A masked data training paradigm for diffusion llms.arXiv preprint arXiv:2603.15803

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:46:21.788600Z

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 bb4a4a1b-0ac1-4693-a199-1f46df8e14f9 · outbound

This paper cites Decoding large language diffusion models with foreseeing movement.arXiv preprint arXiv:2512.04135.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Decoding large language diffusion models with foreseeing movement.arXiv preprint arXiv:2512.04135

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:46:21.926515Z

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 c87c49f0-f142-4067-aa60-f7ace27a3b88 · outbound

This paper cites Large Language Diffusion Models.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Large Language Diffusion Models

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-11T16:51:05.252747Z

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 cbbd3274-67b2-4f34-ad19-b85c64b8442e · outbound

This paper cites an unresolved cited work.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-05-26T01:36:29.256149Z

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 f82eec0c-6a4b-490e-9c53-0d880191c33e · outbound

This paper cites Qingyan Wei, Yaojie Zhang, Zhiyuan Liu, Dongrui Liu, and Linfeng Zhang.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Qingyan Wei, Yaojie Zhang, Zhiyuan Liu, Dongrui Liu, and Linfeng Zhang

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T16:46:22.725985Z

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 fd31f20f-0327-41b0-a5ed-1571556980aa · outbound

This paper cites Accelerating diffusion large language models with slowfast sampling: The three golden principles.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Accelerating diffusion large language models with slowfast sampling: The three golden principles

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:51:05.238375Z

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 d507f685-85de-486f-97f1-8560483e4d0d · outbound

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

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Fast-dLLM: Training-free Acceleration of Diffusion LLM by Enabling KV Cache and Parallel Decoding

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-16T04:28:02.518107Z

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 eda0b9a8-b679-4b51-aeae-4c179a44c356 · outbound

This paper cites Time-annealed perturbation sampling: Diverse generation for diffusion language models.arXiv preprint arXiv:2601.22629.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Time-annealed perturbation sampling: Diverse generation for diffusion language models.arXiv preprint arXiv:2601.22629

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T16:46:22.748341Z

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 b19090c8-7d93-4e93-a3d4-73593eb6fc21 · outbound

This paper cites Dream 7B: Diffusion Large Language Models.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Dream 7B: Diffusion Large Language Models

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-11T16:46:23.134278Z

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 caf1c025-8f85-4733-b3c7-6fe00a6e9eec · outbound

This paper cites Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-05-11T16:46:23.325802Z

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 ced0d513-5db4-406d-9b5d-d62a397a8a67 · outbound

This paper cites an unresolved cited work.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-05-26T01:36:29.262054Z

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 dee4acd8-0553-4955-b9ae-5796a9ea8374 · outbound

This paper cites an unresolved cited work.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-05-26T01:36:29.265092Z

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 97bbc998-27e8-45cc-b027-af2a93947599 · outbound

This paper cites Datasets: •GSM8K[Cobbe et al., 2021]: MIT License.

Focus on the Core: Empowering Diffusion Large Language Models by Self-Contrast Datasets: •GSM8K[Cobbe et al., 2021]: MIT License

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T01:36:29.253434Z

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.

Pith citing papers

No inbound Pith citation observations are available.