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Paper Citation Record · LEDGER

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

As of 16 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 16 inbound Pith citation observations for arXiv:2508.08170.

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

pith.paper-citation-record.v1
2508.08170 v2

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:42:32.990372Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T03:16:53.025755Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:59:33.829869Z

Reference resolution

10 of 10 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 65f69500-6aa6-461c-a021-5cc9b0f6d118 · outbound

This paper cites Periodic Vibration Gaussian: Dynamic Urban Scene Reconstruction and Real-time Rendering.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction Periodic Vibration Gaussian: Dynamic Urban Scene Reconstruction and Real-time Rendering

Reference 3

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no resolver link, observed 2026-08-05T21:42:32.408236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:42:32.408236Z digest=sha256:b1048c7b2f1afbb48f80312d6d34ec340585db3725229a10cad9c54994436680

Observation 376e100a-c07a-44cf-a3ed-b20f5cabf601 · outbound

This paper cites YOLOv11: An Overview of the Key Architectural Enhancements.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction YOLOv11: An Overview of the Key Architectural Enhancements

Reference 6

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no resolver link, observed 2026-08-05T21:42:32.645426Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:42:32.645426Z digest=sha256:97b4e89201917e9ceec4a1afdf27e58c8bb131722ab7f99f7bbffb2b859fd392

Observation 03c2bda3-6ee2-43fb-a09d-630724e5fa88 · outbound

This paper cites Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction Street Gaussians: Modeling Dynamic Urban Scenes with Gaussian Splatting

Reference 9

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no resolver link, observed 2026-08-05T21:42:32.924501Z

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source=pdf_text observed=2026-08-05T21:42:32.924501Z digest=sha256:c3986931aefa07d523e293eac6062bdfdcb7a8c8df6f6d92ad94d134f19d38ea

Observation 6a8960dc-8b8f-44f1-9177-ed9f24c14839 · outbound

This paper cites DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction DiffusionAD: Norm-guided One-step Denoising Diffusion for Anomaly Detection

Reference 10

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no resolver link, observed 2026-08-05T21:42:32.990372Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:42:32.990372Z digest=sha256:95176ad573eba43cbd7e15877788231e0fc5403613f372eeb552772c6aab85a6

Observation 2f48b743-8203-4f8d-b8d1-acca1f12993a · outbound

This paper cites Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation

Reference 158

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no resolver link, observed 2026-08-05T21:42:32.734655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:42:32.734655Z digest=sha256:9bc1d75450a6105b288b97e6352d99460fd8a26c1babd06b88b6c4be60dd88ec

Observation fae43f99-67e5-49ec-9452-729171faf3d3 · outbound

This paper cites CARIL: Confidence-Aware Regression in Imitation Learning for Autonomous Driving.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction CARIL: Confidence-Aware Regression in Imitation Learning for Autonomous Driving

Reference 2019

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local_arxiv, observed 2026-08-05T21:42:33.209972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-05T21:42:32.523132Z digest=sha256:caada61378c69d50297bbc5a6f93b60ecaa30e156347e90d563c17335bf9d6a8

Observation c78a6916-196c-4a98-97ad-70ee81e84fb6 · outbound

This paper cites NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles

Reference 2020

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source=pdf_text observed=2026-08-05T21:42:32.246311Z digest=sha256:1a565a3a4a236b3f7621ed35e553de056e5ad4d6dfcee01f7b2852084f5c68b4

Observation c4fbbca3-9eb6-4cc7-b5bc-000cd4ffa5a7 · outbound

This paper cites Proximal Policy Optimization Algorithms.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction Proximal Policy Optimization Algorithms

Reference 2021

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no resolver link, observed 2026-08-05T21:42:32.831219Z

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source=pdf_text observed=2026-08-05T21:42:32.831219Z digest=sha256:046ca576f64c0bb0422ee839908107987e34b041443e1ad28bca565c1c2d54aa

Observation 279d2d21-50c6-44b0-99a7-456aca18e8dc · outbound

This paper cites VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

Reference 2023

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no resolver link, observed 2026-08-05T21:42:32.338123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:42:32.338123Z digest=sha256:d99a77aec929f704ad14c08a09031f85a094115184935afc4f0044610ed79987

Observation d6cac206-e277-4931-b6c3-fd8072dbe630 · outbound

This paper cites AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning.

ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning

Reference 2024

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no resolver link, observed 2026-08-05T21:42:32.589217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T21:42:32.589217Z digest=sha256:2708a4190254322a754393a2265561a01c4c09c589f40eed203feb6cbd1d7caa

Pith citing papers

Observation 2de14ce3-b88a-4848-b897-51fdbfbe6f2c · inbound

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World cites this paper.

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 55

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arxiv_id, observed 2026-05-16T19:38:21.046767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-16T19:34:39.518649Z digest=sha256:88fb8e3d2ffab26dabe5455f06fb6a0cecdcfaf86366285323cb7f45fa7a05c4

Observation 6a686d4f-928f-471a-b489-c0224f0f33b7 · inbound

VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis cites this paper.

VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 47

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arxiv_id, observed 2026-05-11T07:11:01.202677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T17:16:31.378588Z digest=sha256:6bfd296d22aab05dc57df913e42f7d97f8ed93088743ec9c56c16fe32e293ec2

Observation 05b8a0cf-1afc-4b54-86f9-405ab8630d57 · inbound

BridgeSim: Unveiling the OL-CL Gap in End-to-End Autonomous Driving cites this paper.

BridgeSim: Unveiling the OL-CL Gap in End-to-End Autonomous Driving ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 31

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arxiv_id, observed 2026-05-11T11:16:08.930209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T15:03:02.833156Z digest=sha256:6b17ad7680856adb8972616941780f3ceff62fb2291c4199b285cdf229a79c9c

Observation bec0fbcf-48ea-4449-8ea9-80319859acf8 · inbound

RAD-2: Scaling Reinforcement Learning in a Generator-Discriminator Framework cites this paper.

RAD-2: Scaling Reinforcement Learning in a Generator-Discriminator Framework ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 40

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arxiv_id, observed 2026-05-10T11:50:21.155676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T11:40:26.649975Z digest=sha256:a4feebdcab5f3e5668d1c8f40cc43b1ff07d62ca063cc1cdde2d661f64a51764

Observation d00e34b6-2ac0-4231-9dfd-d3f38b5c1339 · inbound

ReTrack: Evidence-Driven Dual-Stream Directional Anchor Calibration Network for Composed Video Retrieval cites this paper.

ReTrack: Evidence-Driven Dual-Stream Directional Anchor Calibration Network for Composed Video Retrieval ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 27

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arxiv_id, observed 2026-05-10T12:05:23.111362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T04:41:23.980996Z digest=sha256:cf5deb1bf8cd11931fe0e8a56171804595280f8e163897aaee792d0d7f4594c9

Observation cf11be99-dd01-479a-84f0-a798668ed94c · inbound

HABIT: Chrono-Synergia Robust Progressive Learning Framework for Composed Image Retrieval cites this paper.

HABIT: Chrono-Synergia Robust Progressive Learning Framework for Composed Image Retrieval ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 130

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arxiv_id, observed 2026-05-10T11:30:19.982501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T04:50:51.806532Z digest=sha256:46ee2c2e766ef651481233489bf89c05f81d7cd089b3b45f56da619e641fb9be

Observation 49776a9e-4714-4746-81b5-cb842a0eca41 · inbound

INTENT: Invariance and Discrimination-aware Noise Mitigation for Robust Composed Image Retrieval cites this paper.

INTENT: Invariance and Discrimination-aware Noise Mitigation for Robust Composed Image Retrieval ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 5

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arxiv_id, observed 2026-05-10T12:05:22.678618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-10T04:41:57.207279Z digest=sha256:99af5180ae7470d9ed93ddbee49d937a64e999171c32bb4989c0fd18aef2bc95

Observation cb2ef423-00e6-4cd5-9941-b0ca0ad933aa · inbound

GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment cites this paper.

GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 16

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arxiv_id, observed 2026-05-12T10:21:30.690327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-07T06:23:39.902215Z digest=sha256:c1782f0fddd4e24104e8a6ea3a08439369e1bb55e494805c874076b39efc84ee

Observation 4ad210c9-151e-493c-a56c-62ce900be985 · inbound

GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment cites this paper.

GSDrive: Reinforcing Driving Policies by Multi-mode Future Trajectory Probing with 3D Gaussian Splatting Environment ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 16

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arxiv_id, observed 2026-05-19T16:47:39.973304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-19T16:47:09.487360Z digest=sha256:2f5ff03be70906c5b12fba89ce9ada1f64d7da7a6195e8be29e350186b0d5fa0

Observation c3b6f729-5c2f-4b65-a2ce-efd1bd22578b · inbound

CRAFT: Counterfactual-to-Interactive Reinforcement Fine-Tuning for Driving Policies cites this paper.

CRAFT: Counterfactual-to-Interactive Reinforcement Fine-Tuning for Driving Policies ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 28

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arxiv_id, observed 2026-05-11T17:41:06.638765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-08T17:20:55.364175Z digest=sha256:81d14c665c237894e27d5222f3cf6c15b781a6e3aa29c890be426ae754159801

Observation 06ec848d-4bbc-4f4c-812a-e730aba0f7b8 · inbound

Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends cites this paper.

Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 159

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arxiv_id, observed 2026-07-01T21:06:14.184729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T17:29:18.513507Z digest=sha256:e348324640f4a2f5512e602ec374dc9fd529c05b117fa3261b3248104a93c5bb

Observation db616bb0-95f7-4f6a-851d-24d6f41fb599 · inbound

Scaling Self-Play for End-to-End Driving cites this paper.

Scaling Self-Play for End-to-End Driving ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 48

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arxiv_id, observed 2026-07-04T01:29:22.354375Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-26T20:22:03.938518Z digest=sha256:3379ebf71509e7096b78893bc1bd375e49580c789692411c52fedf73d78a724d

Observation d20960fd-955c-4e5c-9429-125f284ea59a · inbound

World Engine: Towards the Era of Post-Training for Autonomous Driving cites this paper.

World Engine: Towards the Era of Post-Training for Autonomous Driving ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 105

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verified exact
arxiv_id, observed 2026-07-04T03:59:33.832183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-26T17:21:15.456982Z digest=sha256:13a1e7abac199752c8e4655db0e9ae06fcbed71c2031d2e1758f2c3167c952a7

Observation 3455965d-697c-408c-911e-7879b5367f59 · inbound

ReWorld: Learning Better Representations for World Action Models cites this paper.

ReWorld: Learning Better Representations for World Action Models ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 20

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verified exact
arxiv_id, observed 2026-07-01T18:25:58.394390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-29T01:58:46.435886Z digest=sha256:2fd2882a3713a8127cd754539b61ecb65a914028d2be6a133d365ad3d71e9614

Observation 59cee31d-d295-4633-a340-a05f9727f6d8 · inbound

GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation cites this paper.

GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 90

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no resolver link, observed 2026-07-12T08:04:48.963890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:04:48.963890Z digest=sha256:974a9300bb6e3c3a08adc74003490875ba01d6dfbbd1af05872e2ef78be69258

Observation 59813907-6f9a-448b-bee4-86275d0e5643 · inbound

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch cites this paper.

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction

Reference 30

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unresolved
no resolver link, observed 2026-08-02T03:16:53.025755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T03:16:53.025755Z digest=sha256:69b1865f59ff10c2436ef1fed661d1e2d85bb8ed46802c8e6da9f6606af1eb92