Paper Citation Record · LEDGER

DiPOD: Diffusion Policy Optimization without Drifting Apart

As of 11 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2606.13795.

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

pith.paper-citation-record.v1
2606.13795 v2

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T07:06:28.426709Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

30 of 30 outbound references displayed

verified exact22
verified fuzzy0
unresolved6
parse uncertain0
malformed identifier1
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 960b7e7c-b54b-4f7f-bbee-41bc7b37dc36 · outbound

This paper cites GR00T N1: An Open Foundation Model for Generalist Humanoid Robots.

DiPOD: Diffusion Policy Optimization without Drifting Apart GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.946121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a22fbede-cd96-4da3-a2c9-e8bb06fef7f0 · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

DiPOD: Diffusion Policy Optimization without Drifting Apart $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 3

Resolution: malformed identifier; local_arxiv, observed 2026-07-03T14:18:22.928069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dfaa3aec-2983-4e79-b3b5-12ef839f308b · outbound

This paper cites DFlash: Block Diffusion for Flash Speculative Decoding.

DiPOD: Diffusion Policy Optimization without Drifting Apart DFlash: Block Diffusion for Flash Speculative Decoding

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T14:18:22.982158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 107974ec-2f41-4bf2-a137-1ae970526c6f · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

DiPOD: Diffusion Policy Optimization without Drifting Apart Training Verifiers to Solve Math Word Problems

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.925727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation aa89b0eb-d069-4902-a6f1-8c0dbf805984 · outbound

This paper cites EXPO: Stable Reinforcement Learning with Expressive Policies.

DiPOD: Diffusion Policy Optimization without Drifting Apart EXPO: Stable Reinforcement Learning with Expressive Policies

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.979890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f34234b6-1274-43aa-baf0-8d82665e6cc1 · outbound

This paper cites IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies.

DiPOD: Diffusion Policy Optimization without Drifting Apart IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.965715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7016376a-1395-4f43-a273-9b4b3513c35c · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

DiPOD: Diffusion Policy Optimization without Drifting Apart Imagen Video: High Definition Video Generation with Diffusion Models

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.968033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2b29a6f0-c9f7-4fef-beb7-ffc3689111d0 · outbound

This paper cites Q-learning with Adjoint Matching.

DiPOD: Diffusion Policy Optimization without Drifting Apart Q-learning with Adjoint Matching

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.970338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c4e80b62-0b03-4115-ba8e-966dfc9001e4 · outbound

This paper cites Reinforcement Learning with Action Chunking.

DiPOD: Diffusion Policy Optimization without Drifting Apart Reinforcement Learning with Action Chunking

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.963367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bf5b6a4e-37b3-4eb4-9983-2349a56664a5 · outbound

This paper cites Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone.

DiPOD: Diffusion Policy Optimization without Drifting Apart Policy Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:18:22.948665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 644ab85c-d687-4f57-9b97-ce1248b4bbbe · outbound

This paper cites Flow Matching Policy Gradients.

DiPOD: Diffusion Policy Optimization without Drifting Apart Flow Matching Policy Gradients

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:18:22.932973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2b9f8ef1-dd90-43e7-bad7-8bb15d3e9c48 · outbound

This paper cites Large Language Diffusion Models.

DiPOD: Diffusion Policy Optimization without Drifting Apart Large Language Diffusion Models

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.961036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9f694d9c-246a-488f-b50c-04c35aba46ff · outbound

This paper cites Diffusion Policy Policy Optimization.

DiPOD: Diffusion Policy Optimization without Drifting Apart Diffusion Policy Policy Optimization

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.958694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 741582ff-527d-43e1-a9b0-30a634f53803 · outbound

This paper cites Proximal Policy Optimization Algorithms.

DiPOD: Diffusion Policy Optimization without Drifting Apart Proximal Policy Optimization Algorithms

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.977532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7c3e0754-8852-4ef0-911e-0011faceacf9 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

DiPOD: Diffusion Policy Optimization without Drifting Apart DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.975130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0490dc30-4fa1-46f9-9922-76ad4b0bb0d1 · outbound

This paper cites Parrot: Data-Driven Behavioral Priors for Reinforcement Learning.

DiPOD: Diffusion Policy Optimization without Drifting Apart Parrot: Data-Driven Behavioral Priors for Reinforcement Learning

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:18:22.938679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c428be7f-c122-4f48-b4a8-844c4293810c · outbound

This paper cites Denoising Diffusion Implicit Models.

DiPOD: Diffusion Policy Optimization without Drifting Apart Denoising Diffusion Implicit Models

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.972624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b47c0824-bb87-4ed6-b25d-44a113ac9537 · outbound

This paper cites Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference.

DiPOD: Diffusion Policy Optimization without Drifting Apart Seed Diffusion: A Large-Scale Diffusion Language Model with High-Speed Inference

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.930438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation eb61d956-522b-4463-9064-0dda553ee36d · outbound

This paper cites wd1: Weighted policy optimization for reasoning in diffusion language models.arXiv preprint arXiv:2507.08838.

DiPOD: Diffusion Policy Optimization without Drifting Apart wd1: Weighted policy optimization for reasoning in diffusion language models.arXiv preprint arXiv:2507.08838

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:18:22.936071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7c67e3c6-2da7-41d7-bd19-863e76a4da89 · outbound

This paper cites SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models.

DiPOD: Diffusion Policy Optimization without Drifting Apart SPG: Sandwiched Policy Gradient for Masked Diffusion Language Models

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.956407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 705f7fe2-ec23-4009-b52d-3b27e673a867 · outbound

This paper cites Dream-Coder 7B: An Open Diffusion Language Model for Code.

DiPOD: Diffusion Policy Optimization without Drifting Apart Dream-Coder 7B: An Open Diffusion Language Model for Code

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:18:22.941284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 95866b58-e1d8-4d40-9303-159209c7b898 · outbound

This paper cites MMaDA: Multimodal Large Diffusion Language Models.

DiPOD: Diffusion Policy Optimization without Drifting Apart MMaDA: Multimodal Large Diffusion Language Models

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:18:22.943777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 32b5ea62-73c1-44c0-8797-b94df4ebc65b · outbound

This paper cites Flow policy gradients for robot control.

DiPOD: Diffusion Policy Optimization without Drifting Apart Flow policy gradients for robot control

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:18:22.951369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0172605a-8bac-4417-a5f9-dfbc82e844bb · outbound

This paper cites d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning.

DiPOD: Diffusion Policy Optimization without Drifting Apart d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-03T14:18:22.953989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f4a60010-8b8c-40e2-9770-f1d742b55638 · outbound

This paper cites an unresolved cited work.

DiPOD: Diffusion Policy Optimization without Drifting Apart Unresolved cited work

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-27T07:06:28.426709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee9e2e89-74e5-42e6-b1c4-873b56624781 · outbound

This paper cites The environment transitions to state st+1 ∼P(·|s t, at), and gives the agent a reward rt =r(s t, at).

DiPOD: Diffusion Policy Optimization without Drifting Apart The environment transitions to state st+1 ∼P(·|s t, at), and gives the agent a reward rt =r(s t, at)

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-27T07:06:28.426709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e22934e3-26cb-4881-a589-4491db5d6669 · outbound

This paper cites SPG [Wang et al., 2025] obtains a practical EUBO surrogate for masked dLLMs by exploiting the special absorbing-mask forward process.

DiPOD: Diffusion Policy Optimization without Drifting Apart SPG [Wang et al., 2025] obtains a practical EUBO surrogate for masked dLLMs by exploiting the special absorbing-mask forward process

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-27T07:06:28.426709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74d6f7ac-cbfc-482d-a8f4-7f0b43bde1ca · outbound

This paper cites This proves Equation (26).

DiPOD: Diffusion Policy Optimization without Drifting Apart This proves Equation (26)

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-27T07:06:28.426709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 340379b8-429d-46aa-937b-f9a255adaf79 · outbound

This paper cites Algorithm implementation.We implement FPO by updating the model parameters according to Equation (4), and SPG by updating the model parameters according to Equation (5).

DiPOD: Diffusion Policy Optimization without Drifting Apart Algorithm implementation.We implement FPO by updating the model parameters according to Equation (4), and SPG by updating the model parameters according to Equation (5)

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-27T07:06:28.426709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6a5c6ae-62b7-4327-a5df-1e088123639c · outbound

This paper cites Although SPG+DiPOD does not show a clear improvement at sequence lengths128 and 512, it is the only setting that reaches the near-100%regime in the zero-shot setting.

DiPOD: Diffusion Policy Optimization without Drifting Apart Although SPG+DiPOD does not show a clear improvement at sequence lengths128 and 512, it is the only setting that reaches the near-100%regime in the zero-shot setting

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-27T07:06:28.426709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.