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Paper Citation Record · LEDGER

The Ingredients for Robotic Diffusion Transformers

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2410.10088.

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

pith.paper-citation-record.v1
2410.10088 v1

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:25:59.736105Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:28:44.419837Z

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Outbound references

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Pith citing papers

Observation 5f2259e8-530b-4653-bd43-293ae5ce9657 · inbound

DexVLA: Vision-Language Model with Plug-In Diffusion Expert for General Robot Control cites this paper.

DexVLA: Vision-Language Model with Plug-In Diffusion Expert for General Robot Control The Ingredients for Robotic Diffusion Transformers

Reference 58

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arxiv_id, observed 2026-05-14T19:48:48.863458Z

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.

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Observation bbbbdc26-b53f-497b-a164-1b338f39e95c · inbound

Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets cites this paper.

Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets The Ingredients for Robotic Diffusion Transformers

Reference 16

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arxiv_id, observed 2026-05-13T16:25:00.442753Z

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=2026-05-13T16:25:00.365534Z digest=sha256:341b0e7a4e9db7ee40cefa4f0794c65dd64645af701ff5564d55d111b5eece1e

Observation be950bdd-6c22-4ced-8164-733187ea9338 · inbound

ChatVLA-2: Vision-Language-Action Model with Open-World Embodied Reasoning from Pretrained Knowledge cites this paper.

ChatVLA-2: Vision-Language-Action Model with Open-World Embodied Reasoning from Pretrained Knowledge The Ingredients for Robotic Diffusion Transformers

Reference 38

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Unavailable: canonical work link unavailable.

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Observation c93e4b73-f8fe-4216-9d4e-9d84582ae2af · inbound

Steering Your Diffusion Policy with Latent Space Reinforcement Learning cites this paper.

Steering Your Diffusion Policy with Latent Space Reinforcement Learning The Ingredients for Robotic Diffusion Transformers

Reference 19

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arxiv_id, observed 2026-05-17T21:55:46.450038Z

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=2026-05-17T21:55:46.183007Z digest=sha256:f986665f1ae836faf19438af78de5d7de5f655e580160ac00b63e40b283de523

Observation ef579c6d-ab4d-43b3-84fd-1ee3b1709d66 · inbound

Behavioral Exploration: Learning to Explore via In-Context Adaptation cites this paper.

Behavioral Exploration: Learning to Explore via In-Context Adaptation The Ingredients for Robotic Diffusion Transformers

Reference 2021

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no resolver link, observed 2026-08-06T18:15:43.506860Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:15:43.506860Z digest=sha256:eaf70ddbe44b891aa1c2f7ff15d74804b5022e62bd910a6a8f8f44ef3ae20913

Observation e8123e6b-2b52-4e9e-a3d2-44304ba05c13 · inbound

Train-Once Plan-Anywhere Kinodynamic Motion Planning via Diffusion Trees cites this paper.

Train-Once Plan-Anywhere Kinodynamic Motion Planning via Diffusion Trees The Ingredients for Robotic Diffusion Transformers

Reference 59

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no resolver link, observed 2026-08-05T14:42:40.242489Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:42:40.242489Z digest=sha256:fb4ace8856ab6374837aaf754d329ab4553da6fdec48ba2fbea43d8bc741f10d

Observation acbb358e-8687-4a4d-adf2-e60bfd6fb463 · inbound

ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training cites this paper.

ManiFlow: A General Robot Manipulation Policy via Consistency Flow Training The Ingredients for Robotic Diffusion Transformers

Reference 34

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no resolver link, observed 2026-08-05T12:15:01.378751Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T12:15:01.378751Z digest=sha256:7c3ddd2ef5b6497ad74cb50d3d9894b70e27f29811d29736b103aa2bb486b063

Observation d9348e4f-afa2-418d-8cf8-c63b781aaed2 · inbound

FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Action Flow Policies cites this paper.

FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Action Flow Policies The Ingredients for Robotic Diffusion Transformers

Reference 42

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no resolver link, observed 2026-08-05T05:48:48.076241Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:48:48.076241Z digest=sha256:81d9404454a7c7ce38c51fdab0bf25146ce39ac403d2eb5bfb90ab54e466f6b8

Observation b282efbf-b2de-490e-b5e6-226a8fec9e41 · inbound

Boosting Embodied AI Agents through Perception-Generation Disaggregation and Asynchronous Pipeline Execution cites this paper.

Boosting Embodied AI Agents through Perception-Generation Disaggregation and Asynchronous Pipeline Execution The Ingredients for Robotic Diffusion Transformers

Reference 18

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no resolver link, observed 2026-08-04T18:58:12.622654Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T18:58:12.622654Z digest=sha256:b16dd6b084f5faba44836997572a9eaead4a5137bc919bb7f6200e5f3f46a027

Observation 9db57e4e-6995-4942-a7a4-efec148d0b83 · inbound

Hybrid Diffusion for Simultaneous Symbolic and Continuous Planning cites this paper.

Hybrid Diffusion for Simultaneous Symbolic and Continuous Planning The Ingredients for Robotic Diffusion Transformers

Reference 10

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arxiv_id, observed 2026-05-18T13:26:25.079250Z

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.

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Observation df2cc7c7-9f52-487f-90cd-13cfab484e06 · inbound

Think Proprioceptively: State-Grounded Visual Token Selection for VLA Policies cites this paper.

Think Proprioceptively: State-Grounded Visual Token Selection for VLA Policies The Ingredients for Robotic Diffusion Transformers

Reference 6

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no resolver link, observed 2026-08-03T03:56:03.958826Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T03:56:03.958826Z digest=sha256:8e59ea207f0096eae3d3ea1616476caba8f24f7a1efca6550de3e61eb8a4775f

Observation 74f17401-c26e-4be1-a586-dfd32a5173e7 · inbound

A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model cites this paper.

A1: A Fully Transparent Open-Source, Adaptive and Efficient Truncated Vision-Language-Action Model The Ingredients for Robotic Diffusion Transformers

Reference 7

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arxiv_id, observed 2026-05-10T22:50:51.381857Z

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.

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Observation fb309cd3-bbac-41fe-aa61-2115ced6621c · inbound

Key-Gram: Extensible World Knowledge for Embodied Manipulation cites this paper.

Key-Gram: Extensible World Knowledge for Embodied Manipulation The Ingredients for Robotic Diffusion Transformers

Reference 30

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arxiv_id, observed 2026-05-20T09:13:10.149690Z

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.

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Observation d98ae142-eb27-4454-82f9-6c96d3565463 · inbound

Phase-Conditioned Imitation Learning with Autonomous Failure Recovery for Robust Deformable Object Manipulation cites this paper.

Phase-Conditioned Imitation Learning with Autonomous Failure Recovery for Robust Deformable Object Manipulation The Ingredients for Robotic Diffusion Transformers

Reference 5

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arxiv_id, observed 2026-06-29T07:23:13.321382Z

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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=2026-06-29T07:13:46.371380Z digest=sha256:919e361c102f9a61c7123e7fafc7c0737a1d8cdbe27ab20bca404b646bd618e3

Observation d2fae532-1d61-49f7-9e2e-eb779e4d8a25 · inbound

General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling cites this paper.

General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling The Ingredients for Robotic Diffusion Transformers

Reference 105

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arxiv_id, observed 2026-06-29T13:33:27.803052Z

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

source=arxiv_source observed=2026-06-29T13:33:03.368006Z digest=sha256:e6245a251a23f4186c86be7f93c6580f86ea6fa10d4b99cc7b23aba8b3389bb4

Observation d5a815f9-be77-4621-93de-617dd9563d51 · inbound

Lagrangian Perturbation Diffusion Steering: Latent Reinforcement Learning for Generative Policies cites this paper.

Lagrangian Perturbation Diffusion Steering: Latent Reinforcement Learning for Generative Policies The Ingredients for Robotic Diffusion Transformers

Reference 7

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arxiv_id, observed 2026-06-28T17:22:24.706178Z

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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=2026-06-28T17:19:36.722892Z digest=sha256:9307952db99151aac26dab2e06ead1f81f4ce22756c1391ffa57f04e2c5411ca

Observation e949eaa8-f466-4d7a-b570-e3b92e6100ef · inbound

Multi-Resolution Tactile Imitation Learning for Contact-Rich Robotic Manipulation cites this paper.

Multi-Resolution Tactile Imitation Learning for Contact-Rich Robotic Manipulation The Ingredients for Robotic Diffusion Transformers

Reference 48

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verified exact
arxiv_id, observed 2026-07-02T13:46:59.693372Z

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=2026-06-28T00:58:25.323475Z digest=sha256:7e2174616b682887f58e2bf07767325f5238905521904c6e01a2144a6ede6863

Observation de5b2c95-5852-4fd9-ad7b-1a9ee37f2856 · inbound

Unified Motion-Action Modeling for Heterogeneous Robot Learning cites this paper.

Unified Motion-Action Modeling for Heterogeneous Robot Learning The Ingredients for Robotic Diffusion Transformers

Reference 45

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verified exact
arxiv_id, observed 2026-07-03T17:28:44.421282Z

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=2026-06-27T04:09:06.885372Z digest=sha256:d1085e5c2c40d6b69118ca3eadce893196ade1f31ef0280deb30f7df15aa98a1

Observation 7a890ec2-60b0-44e5-8b94-5278e61d12cb · inbound

Differential Amplifier-Inspired AmpAttention for Multi-View Robotic Manipulation cites this paper.

Differential Amplifier-Inspired AmpAttention for Multi-View Robotic Manipulation The Ingredients for Robotic Diffusion Transformers

Reference 15

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no resolver link, observed 2026-07-12T06:39:16.303751Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T06:39:16.303751Z digest=sha256:5af133418f443c3e990060e2bc5811077e3abc688a1189c5e5fb80b2ef73d4c0

Observation 865b414c-3d25-489f-86a7-23d0f25c4128 · inbound

Why Does Action Chunking Improve Behavioral Cloning Performance in Robotic Control? cites this paper.

Why Does Action Chunking Improve Behavioral Cloning Performance in Robotic Control? The Ingredients for Robotic Diffusion Transformers

Reference 23

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