Paper Citation Record · LEDGER

DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2503.12170.

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

pith.paper-citation-record.v1
2503.12170 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:32:52.419878Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:30:08.067230Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 506f9c3f-e701-4a45-a2c6-4d4f8eb3e1da · inbound

Fully Unified Motion Planning for End-to-End Autonomous Driving cites this paper.

Fully Unified Motion Planning for End-to-End Autonomous Driving DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-16T12:32:52.419878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61f80b15-e8dd-42e1-91b0-3615917a15d2 · inbound

DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving cites this paper.

DriveMoE: Mixture-of-Experts for Vision-Language-Action Model in End-to-End Autonomous Driving DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:31:40.630938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 07158961-601c-4f08-91d1-66b2a1065106 · inbound

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving cites this paper.

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-19T06:07:07.230638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d1b9ffd2-ca2b-4d4f-9255-b3797adaf89c · inbound

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving cites this paper.

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T20:04:09.798398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c923041a-47e3-483b-b181-4df2ee73239a · inbound

MindDrive: A Vision-Language-Action Model for Autonomous Driving via Online Reinforcement Learning cites this paper.

MindDrive: A Vision-Language-Action Model for Autonomous Driving via Online Reinforcement Learning DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-03T16:27:27.595428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef1c6fd2-528f-4e2b-bb82-5e114ea3ad92 · inbound

AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving cites this paper.

AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-16T18:41:11.148195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d1cf2f1c-fd20-4b2f-815a-631a1c84933d · inbound

AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving cites this paper.

AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T12:48:36.246107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6929fab5-c36c-4ec7-b8d2-d281daf21677 · inbound

Deconfounded Lifelong Learning for Autonomous Driving via Dynamic Knowledge Spaces cites this paper.

Deconfounded Lifelong Learning for Autonomous Driving via Dynamic Knowledge Spaces DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 49

Resolution: unresolved; no resolver link, observed 2026-07-14T21:21:10.946939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97ac8240-9be0-4020-8a45-e89130ed3f6c · inbound

LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving cites this paper.

LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 50

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:31:01.154664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 98709980-b71b-4225-bfd3-754e109b314c · inbound

ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation cites this paper.

ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 48

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:26:27.485706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 74dbd384-e03a-4c2f-a581-308ee29493de · inbound

UniTeD: Unified Temporal Diffusion for Joint Perception and Planning in Autonomous Driving cites this paper.

UniTeD: Unified Temporal Diffusion for Joint Perception and Planning in Autonomous Driving DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 53

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T19:30:08.068600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b1627491-6407-4f4f-8695-df2ba1d3db89 · inbound

OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model cites this paper.

OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-06-30T06:04:21.633952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad49adf5-d077-4d96-9fff-96dec4a86855 · inbound

Off the Rails: Hijacking the Scoring Head in Generative End-to-End Driving Planners with Safety-Violating Adversarial Perturbations cites this paper.

Off the Rails: Hijacking the Scoring Head in Generative End-to-End Driving Planners with Safety-Violating Adversarial Perturbations DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-07-01T12:55:44.560754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation aad98c4d-102f-481e-ab1f-e62ed70b3ae9 · inbound

MOJITO: Modal Joint Learning for Unified End-to-End Autonomous Driving cites this paper.

MOJITO: Modal Joint Learning for Unified End-to-End Autonomous Driving DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-30T20:32:30.470495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e249aa0-7648-4181-9521-f5b26bca1a21 · inbound

WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLA cites this paper.

WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLA DiffAD: A Unified Diffusion Modeling Approach for Autonomous Driving

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-06T00:41:00.796566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.