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Paper Citation Record · LEDGER

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation

As of 22 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 3 inbound Pith citation observations for arXiv:2506.01121.

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

pith.paper-citation-record.v1
2506.01121 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:58:41.014414Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:19:17.181437Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T21:27:47.930306Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact3
  • verified fuzzy5
  • unresolved20
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b9815d1-7cfe-4239-befc-5dd9fc583f89 · outbound

This paper cites an unresolved cited work.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Unresolved cited work

Reference 3

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verified exact
doi, observed 2026-08-07T11:58:41.531075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation fee70fe5-2ac7-4a87-a656-0c119e026cf3 · outbound

This paper cites Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:58:38.046303Z digest=sha256:694f2647409ad10458ce8191ed6cb89561e08fcab6cbc770dfcffad4042f81ac

Observation f008caed-382e-4b3a-a63e-cd98722f6dd0 · outbound

This paper cites RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 10325462-bcba-4d24-8f17-1eee6fb351e6 · outbound

This paper cites Categorical Reparameterization with Gumbel-Softmax.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Categorical Reparameterization with Gumbel-Softmax

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:58:38.460561Z digest=sha256:631ed93215d6f1c0e2e9e00eb5effd21b53ad05467238a109e9ea5e0396c2e13

Observation 102fd97b-9ac6-44f6-9782-613ddc5f265e · outbound

This paper cites Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

Reference 11

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:58:38.829122Z digest=sha256:dddc98791203c706d61e0773ff0d5861655b81f93b8c513eea813889e6923a43

Observation 2fd5c52c-d172-4293-aa42-77d8918b4fe0 · outbound

This paper cites Do generative video models understand physical principles?.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Do generative video models understand physical principles?

Reference 12

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source=pdf_text observed=2026-08-07T11:58:38.971134Z digest=sha256:02a0074878d8f55776073b4137a5548b61479e0dbfb5483f4be261c8642f9e94

Observation 116a7287-594a-4bf1-8fcc-fc08a0b12510 · outbound

This paper cites Jailbreaking LLM-Controlled Robots.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Jailbreaking LLM-Controlled Robots

Reference 16

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source=pdf_text observed=2026-08-07T11:58:39.441328Z digest=sha256:2907854d97526e3828623bd1402849a1fdc46c4e620d0eebb5f9885e04c0525a

Observation cf80086b-d4aa-4243-9be7-12790735844a · outbound

This paper cites Simple Guidance Mechanisms for Discrete Diffusion Models.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Simple Guidance Mechanisms for Discrete Diffusion Models

Reference 18

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no resolver link, observed 2026-08-07T11:58:39.631865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5e93fffd-6830-4c1a-893f-8a2f2cb597bb · outbound

This paper cites Multi-Robot Motion Planning with Diffusion Models.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Multi-Robot Motion Planning with Diffusion Models

Reference 19

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no resolver link, observed 2026-08-07T11:58:39.775224Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:58:39.775224Z digest=sha256:48278d08dd48048b0927f664237a60998faf1041de1026cf793e0b9a880b2281

Observation 2f05b2cf-118d-4e44-8d93-9f41711ae293 · outbound

This paper cites Towards safe autonomous driving policies using a neuro-symbolic deep reinforcement learning approach.arXiv preprint arXiv:2307.01316,.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Towards safe autonomous driving policies using a neuro-symbolic deep reinforcement learning approach.arXiv preprint arXiv:2307.01316,

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 91e6ab75-19c2-43c1-9473-eeb269237b41 · outbound

This paper cites Simplified and Generalized Masked Diffusion for Discrete Data.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Simplified and Generalized Masked Diffusion for Discrete Data

Reference 21

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no resolver link, observed 2026-08-07T11:58:40.051599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:58:40.051599Z digest=sha256:c7c84b274b71b722735832948dccbd0f2ad6c9be1e50cc599f351e105fc618a8

Observation 4dc3b8ac-95e0-424f-955b-663718d451c2 · outbound

This paper cites DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models

Reference 23

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation c2fd90b1-a4a2-4072-a72b-385daf4b7bb4 · outbound

This paper cites Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling

Reference 24

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unresolved
no resolver link, observed 2026-08-07T11:58:40.357177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:58:40.357177Z digest=sha256:9d741fcee6b21bcb7ab9298722c3d7f6e7f790ccd5fa854a057e27ee3dcbf9bd

Observation a506dee4-a07f-495b-9421-a60413221e08 · outbound

This paper cites an unresolved cited work.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Unresolved cited work

Reference 25

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raw_fallback, observed 2026-08-07T11:58:43.751330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 9cf38af2-61f9-45f9-9826-89823d1e4428 · outbound

This paper cites an unresolved cited work.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Unresolved cited work

Reference 26

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raw_fallback, observed 2026-08-07T11:58:43.449877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 1b88098b-0b2c-4881-943d-686679f13f63 · outbound

This paper cites flip costs.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation flip costs

Reference 27

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f28c8a30-7fb4-48df-b439-53a655538611 · outbound

This paper cites three-membered heterocycle.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation three-membered heterocycle

Reference 28

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation e1dd1e24-051a-4fc2-8c76-d1fa763613b2 · outbound

This paper cites This is particularly exasperated as we scale the number of agents and obstacles.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation This is particularly exasperated as we scale the number of agents and obstacles

Reference 29

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raw_fallback, observed 2026-08-07T11:58:42.584760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation d691c0eb-2381-4b2c-8b80-a6543b189130 · outbound

This paper cites The conditional model is implemented following V oleti et al.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation The conditional model is implemented following V oleti et al

Reference 30

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 22575156-c22d-47ad-b569-6be41446a456 · outbound

This paper cites Motion planning diffusion: Learning and planning of robot motions with diffusion models.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Motion planning diffusion: Learning and planning of robot motions with diffusion models

Reference 2002

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no resolver link, observed 2026-08-07T11:58:37.627319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 825c281e-271c-4174-9368-3695d89a34c3 · outbound

This paper cites Simple and Effective Masked Diffusion Language Models.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Simple and Effective Masked Diffusion Language Models

Reference 2012

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no resolver link, observed 2026-08-07T11:58:39.561862Z

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Observation fa5303d9-91a3-4ce5-9e35-018d631247a0 · outbound

This paper cites Alexander Robey, Zachary Ravichandran, Vijay Kumar, Hamed Hassani, and George J.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Alexander Robey, Zachary Ravichandran, Vijay Kumar, Hamed Hassani, and George J

Reference 2014

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Observation aa2df788-0862-4ea6-a5b7-813c4a8482f8 · outbound

This paper cites Scalfani, Rachel Walker, Kazuya Uji- hara, Daniel Probst, Juuso Lehtivarjo, Hussein Faara, guillaume godin, Axel Pahl, and Jeremy Monat.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Scalfani, Rachel Walker, Kazuya Uji- hara, Daniel Probst, Juuso Lehtivarjo, Hussein Faara, guillaume godin, Axel Pahl, and Jeremy Monat

Reference 2016

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ba250b02-8c1f-4d1e-8eac-97e0f4a170e9 · outbound

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

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Score-Based Generative Modeling through Stochastic Differential Equations

Reference 2019

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Unavailable: canonical work link unavailable.

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Observation a0d46fd1-5f1c-438b-bb22-5951a2c717a6 · outbound

This paper cites Plug and Play Language Models: A Simple Approach to Controlled Text Generation.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Plug and Play Language Models: A Simple Approach to Controlled Text Generation

Reference 2020

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c48e0ce3-1856-47cd-ac85-e736203cd40a · outbound

This paper cites Red Teaming Language Models with Language Models.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Red Teaming Language Models with Language Models

Reference 2021

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no resolver link, observed 2026-08-07T11:58:39.102180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:58:39.102180Z digest=sha256:6d2811fba835db8fc40ed431e4b1825e5fce82ca0c8aea6fe681771b11d8e103

Observation cafbf2c3-5b53-4f87-a6ff-d222b696a33c · outbound

This paper cites Sampling constrained tra- jectories using composable diffusion models.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Sampling constrained tra- jectories using composable diffusion models

Reference 2022

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verified fuzzy
raw_fallback, observed 2026-08-07T11:58:44.063463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation f7b710fe-50d9-4110-91c3-906c1a2711f5 · outbound

This paper cites Gradient Guidance for Diffusion Models: An Optimization Perspective.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Gradient Guidance for Diffusion Models: An Optimization Perspective

Reference 2023

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no resolver link, observed 2026-08-07T11:58:38.208407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:58:38.208407Z digest=sha256:bfa81e1c3e087bea35496b9045bfe35de77832ecc39515cdab875a1459509f92

Observation 7f286e9e-abfe-429d-bc17-3a50318e114e · outbound

This paper cites Classifier-Free Diffusion Guidance.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Classifier-Free Diffusion Guidance

Reference 2024

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unresolved
no resolver link, observed 2026-08-07T11:58:38.356525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:58:38.356525Z digest=sha256:1eda3b5df1216d884a2ef800b11b79e488198189909b21103835e14923e811e9

Observation 2e19a9eb-dd36-4424-afd7-680adb26c1f4 · outbound

This paper cites Yixin Liu, Kai Zhang, Yuan Li, Zhiling Yan, Chujie Gao, Ruoxi Chen, Zhengqing Yuan, Yue Huang, Hanchi Sun, Jianfeng Gao, Lifang He, and Lichao Sun.

Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation Yixin Liu, Kai Zhang, Yuan Li, Zhiling Yan, Chujie Gao, Ruoxi Chen, Zhengqing Yuan, Yue Huang, Hanchi Sun, Jianfeng Gao, Lifang He, and Lichao Sun

Reference 2025

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verified exact
doi, observed 2026-08-07T11:58:41.274932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Pith citing papers

Observation 6ae4d008-96ab-45c1-b891-20c4a925b705 · inbound

Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning cites this paper.

Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation

Reference 2024

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no resolver link, observed 2026-08-05T15:19:17.181437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:19:17.181437Z digest=sha256:35af9a1a50fe846b1e71d41c86a104f38c61f95166ed4dd6f44812e54fb5fb42

Observation f8a03f4c-b4dd-4269-b2d4-6528f116c6d3 · inbound

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design cites this paper.

Symbolic Neural Generation with Applications to Lead Discovery in Drug Design Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:59:21.322189Z digest=sha256:52e55e1dfa8ffc12ad59e273f7c3608c32e69e53955902148e7d4a3e3ab5192f

Observation 525a8f74-9410-4914-aa97-5a52cafbdd4a · inbound

Constrained Code Generation with Discrete Diffusion cites this paper.

Constrained Code Generation with Discrete Diffusion Neuro-Symbolic Generative Diffusion Models for Physically Grounded, Robust, and Safe Generation

Reference 19

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verified exact
arxiv_id, observed 2026-05-19T21:27:47.932152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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