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Paper Citation Record · LEDGER

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning

As of 7 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 2 inbound Pith citation observations for arXiv:2507.12977.

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

pith.paper-citation-record.v1
2507.12977 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:38:36.716242Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:34:38.462448Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T02:38:17.343103Z

Reference resolution

49 of 49 outbound references displayed

  • verified exact1
  • verified fuzzy36
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation faf8fca2-41d8-4109-8203-e470469574af · outbound

This paper cites St-p3: End- to-end vision-based autonomous driving via spatial-temporal feature learning,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning St-p3: End- to-end vision-based autonomous driving via spatial-temporal feature learning,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c6ab466e-753e-4f9c-a006-8e9635ed060b · outbound

This paper cites Per- ceive, predict, and plan: Safe motion planning through interpretable semantic representations,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Per- ceive, predict, and plan: Safe motion planning through interpretable semantic representations,

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T16:38:46.831482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 66c0482e-4272-4b80-8524-1b3f73df66bc · outbound

This paper cites Dsdnet: Deep structured self-driving network,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Dsdnet: Deep structured self-driving network,

Reference 3

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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 2026-08-07T06:34:17.273281+00:00.

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Observation 1d7728ca-2930-480e-8e9d-d10de4f472a0 · outbound

This paper cites Multi-modal knowl- edge distillation-based human trajectory forecasting,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Multi-modal knowl- edge distillation-based human trajectory forecasting,

Reference 4

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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 2026-08-07T06:34:17.273281+00:00.

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Observation e5b3705b-37f2-4c92-bb5a-dc368687b641 · outbound

This paper cites Fast-replanning motion control for non-holonomic vehicles with aborting a*,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Fast-replanning motion control for non-holonomic vehicles with aborting a*,

Reference 5

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 22693db8-4841-4acb-8402-031293c46cf0 · outbound

This paper cites Informed rrt*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Informed rrt*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic,

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 7c348d81-fff9-49f8-842a-7c9e1a1ed09e · outbound

This paper cites Path planning using neural a* search,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Path planning using neural a* search,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation a6c96eca-9795-4be6-a548-d90b8f389437 · outbound

This paper cites Sampling-based algorithms for optimal motion planning,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Sampling-based algorithms for optimal motion planning,

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 96472994-1514-49d9-b45a-517e6eb99ca2 · outbound

This paper cites Deep imitation learning for autonomous driving in generic urban scenarios with enhanced safety,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Deep imitation learning for autonomous driving in generic urban scenarios with enhanced safety,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:45.440891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation dd7a703f-1053-4687-8ca0-bb91cc1921d0 · outbound

This paper cites Safe reinforcement learning with stability guarantee for motion planning of autonomous vehicles,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Safe reinforcement learning with stability guarantee for motion planning of autonomous vehicles,

Reference 10

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raw_fallback, observed 2026-08-06T16:38:45.213239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 233752d2-440c-4f18-9d56-686eea03e744 · outbound

This paper cites Parting with misconceptions about learning-based vehicle motion planning,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Parting with misconceptions about learning-based vehicle motion planning,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-06T16:38:44.980803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 424207c6-bbf6-45dd-9d4e-f28c123a3bde · outbound

This paper cites Differentiable Constrained Imitation Learning for Robot Motion Planning and Control.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Differentiable Constrained Imitation Learning for Robot Motion Planning and Control

Reference 12

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unresolved
no resolver link, observed 2026-08-06T16:38:31.433701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 71c2c8ac-a34f-407b-bbaf-910628542620 · outbound

This paper cites Diffusion-es: Gradient-free planning with diffusion for autonomous and instruction-guided driving,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Diffusion-es: Gradient-free planning with diffusion for autonomous and instruction-guided driving,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:44.782389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f4136118-a487-43f7-8e4d-7c557a609ca7 · outbound

This paper cites Motiondiffuser: Controllable multi-agent motion prediction using diffusion,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Motiondiffuser: Controllable multi-agent motion prediction using diffusion,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:44.543937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 56940f92-5fd7-4254-8b75-aed2a20daac9 · outbound

This paper cites Diffusion models beat gans on image synthesis,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Diffusion models beat gans on image synthesis,

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ce492428-58aa-4220-8a1b-5977589a9920 · outbound

This paper cites Language-guided traffic simulation via scene-level diffu- sion,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Language-guided traffic simulation via scene-level diffu- sion,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:44.267630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d1e7c7ef-8d61-4728-8256-36fc0c2fa831 · outbound

This paper cites Safe-sim: Safety-critical closed-loop traffic simulation with diffusion- controllable adversaries,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Safe-sim: Safety-critical closed-loop traffic simulation with diffusion- controllable adversaries,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:43.946422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 40bb854f-01ac-48bd-aa67-351e05df5eba · outbound

This paper cites Fine-Tuning Language Models with Reward Learning on Policy.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Fine-Tuning Language Models with Reward Learning on Policy

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 1404fe10-6cb0-471d-8729-1f59112944bf · outbound

This paper cites Training diffusion models with reinforcement learning,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Training diffusion models with reinforcement learning,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:43.624323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e3af2e56-e04b-48c8-9eb3-fed313891c33 · outbound

This paper cites Denoising diffusion probabilistic models,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Denoising diffusion probabilistic models,

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a0861cf5-8a3e-4acf-b34c-0c0acbb43bd0 · outbound

This paper cites Improved denoising diffusion prob- abilistic models,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Improved denoising diffusion prob- abilistic models,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:43.355616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 6ad6cba7-d1f8-492e-bf7c-8418c0efb21a · outbound

This paper cites Improving transferability for cross- domain trajectory prediction via neural stochastic differential equa- tion,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Improving transferability for cross- domain trajectory prediction via neural stochastic differential equa- tion,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:43.044648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 92f19643-57e4-4231-b71d-872aeed50c45 · outbound

This paper cites Maximum likelihood training of score-based diffusion models,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Maximum likelihood training of score-based diffusion models,

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 022fdce8-2253-41df-84a9-a17987f66f26 · outbound

This paper cites Data-driven Diffusion Models for Enhancing Safety in Autonomous Vehicle Traffic Simulations.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Data-driven Diffusion Models for Enhancing Safety in Autonomous Vehicle Traffic Simulations

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5f04bf3a-a7c5-4256-b534-67cd80d675f5 · outbound

This paper cites Planning with Diffusion for Flexible Behavior Synthesis.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Planning with Diffusion for Flexible Behavior Synthesis

Reference 25

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5a0a298e-080c-43fa-95ac-a15f4603fb61 · outbound

This paper cites Leveraging future relationship reasoning for vehicle trajectory prediction,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Leveraging future relationship reasoning for vehicle trajectory prediction,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:42.507763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4dc59fa4-4fac-47b7-9879-ccd76c0ca9fd · outbound

This paper cites an unresolved cited work.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Unresolved cited work

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 697deb55-7215-4d23-aa20-cd32d652cc1d · outbound

This paper cites Human-level control through deep reinforcement learning,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Human-level control through deep reinforcement learning,

Reference 28

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation bd6870bd-9931-4757-b50a-81e8076a8731 · outbound

This paper cites an unresolved cited work.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Unresolved cited work

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a9ef963a-46d0-4348-8568-0c152cea7b0d · outbound

This paper cites A markovian decision process,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning A markovian decision process,

Reference 30

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:38:33.928478Z digest=sha256:d047760d95e72fec604e72d85ea9e2b981253fa512cfb7d0c56d7a459e1e12bf

Observation 65ec2c56-ae69-4d0d-b0d5-efac8f5567b4 · outbound

This paper cites Deterministic policy gradient algorithms,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Deterministic policy gradient algorithms,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:41.817679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e1163659-b9b2-4450-8d61-959a4728aaa3 · outbound

This paper cites Comprehensive reactive safety: No need for a trajectory if you have a strategy,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Comprehensive reactive safety: No need for a trajectory if you have a strategy,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:41.510705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 43a29ff3-811f-40de-8e6a-cacfe5926601 · outbound

This paper cites Autonomous driving motion planning with constrained iterative lqr,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Autonomous driving motion planning with constrained iterative lqr,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:41.216894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e57640ad-2962-4086-b6e5-013ec4440039 · outbound

This paper cites Leader: Learning attention over driving behaviors for planning under uncertainty,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Leader: Learning attention over driving behaviors for planning under uncertainty,

Reference 34

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 4e2ae681-4809-4b72-8e39-20da45b38e36 · outbound

This paper cites Kb-tree: Learnable and continuous monte- carlo tree search for autonomous driving planning,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Kb-tree: Learnable and continuous monte- carlo tree search for autonomous driving planning,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:40.618371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:34.660594Z digest=sha256:e4bc570aac0950687c53b81befe9fd7c17490da33224241554c804927ce0b954

Observation cc8420a6-6c07-47f9-9e84-c42e8b3b83ea · outbound

This paper cites Driving maneuvers prediction based autonomous driving control by deep monte carlo tree search,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Driving maneuvers prediction based autonomous driving control by deep monte carlo tree search,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:40.307644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:34.837308Z digest=sha256:31677c52ae517b2868a657e2c551f108c422031f8e0e533310c2418afdd8a42a

Observation 5a5bd1f6-1ae4-48ce-8f39-3ec7acbff972 · outbound

This paper cites Crowd-robot interaction: Crowd-aware robot navigation with attention-based deep reinforce- ment learning,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Crowd-robot interaction: Crowd-aware robot navigation with attention-based deep reinforce- ment learning,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:40.057558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:35.004659Z digest=sha256:488204553b053917c862c0dd596ed700e6b3e1ce7f79429fe490a0ab037806ad

Observation 2426f62b-00e3-43c9-bb91-ba36bea1ced6 · outbound

This paper cites Rethinking closed-loop training for autonomous driving,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Rethinking closed-loop training for autonomous driving,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:39.793267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:35.175208Z digest=sha256:845625fa0dad04b695172333f9773e1e2a4e5915dbb7c4a1054edcefc865a0ca

Observation cfa90fd5-bbc6-4a6f-ab0d-a081db8ea412 · outbound

This paper cites UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T16:38:35.279970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:38:35.279970Z digest=sha256:bc8623066657232b781bd676ececec4bbbeab599a988d64c2604bd5bbe40ac64

Observation 5480b033-6841-4eb0-8a9e-36d72bf2e98d · outbound

This paper cites Model-Based Reinforcement Learning for Atari.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Model-Based Reinforcement Learning for Atari

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T16:38:35.402897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:38:35.402897Z digest=sha256:723e1e18f07b929d6cef6669b2964e6237135cbd037910711d9861fe14590cb2

Observation e4b71ebc-b3b0-4a22-97d6-0684ffe7abb5 · outbound

This paper cites Approximately optimal approximate reinforcement learning,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Approximately optimal approximate reinforcement learning,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:39.465099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:35.558259Z digest=sha256:ce792cd541093a959a2029491a4d800a83f1241d3f2ff1243f66cf3ef32a55d7

Observation cfc50aff-d961-484a-8a3a-33a276314092 · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T16:38:35.692097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:38:35.692097Z digest=sha256:409dfe78c0df4c19e0bd33991fc877d9e808fe0bad123c8e0ce7d7b2377332de

Observation 8bee159c-9eb9-454b-ab7e-b295b75b1d86 · outbound

This paper cites You’ll never walk alone: Modeling social behavior for multi-target tracking,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning You’ll never walk alone: Modeling social behavior for multi-target tracking,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:39.188418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:35.873363Z digest=sha256:fa04cca498a15d5bb0edad72b9d5fbcbeb6cf2270b8f89ac65c919e06591b363

Observation b87a31c1-40b2-4398-9c5b-dc162035a206 · outbound

This paper cites Crowds by example,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Crowds by example,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:38.877846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:36.019114Z digest=sha256:2a85001c48f8166feab929004257dc597778868f7005719263087c6126c48651

Observation fbb7d610-3bb4-4584-8ab6-f7114cbe6d42 · outbound

This paper cites A game-theoretic framework for joint forecasting and planning,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning A game-theoretic framework for joint forecasting and planning,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:38.596213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:36.142468Z digest=sha256:fc6edcc6d06c6e5610a4fbbaf8327f96dadc712064173c69c367d195e12cabdb

Observation a8c5f799-b57f-4978-a72f-d43ba4163ddf · outbound

This paper cites Human trajectory prediction via neural social physics,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Human trajectory prediction via neural social physics,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:38.346033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:36.311109Z digest=sha256:936892a2f9d3e15d57bda1160e15ae8cf447ff4789d4f7c83b4261a4cf5ed00a

Observation 36f629b8-3a35-4601-9aa3-1289bb3193c4 · outbound

This paper cites Dtpp: Differentiable joint conditional prediction and cost evaluation for tree policy planning in autonomous driving,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Dtpp: Differentiable joint conditional prediction and cost evaluation for tree policy planning in autonomous driving,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:38.084375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:36.450342Z digest=sha256:28e3d51376201968fae7643f382fbdcf3e6c43cf4a7c542f0f084ae25980d5f0

Observation 18d390bf-2c40-41fc-9771-baac2345d6b5 · outbound

This paper cites Differentiable integrated motion prediction and planning with learnable cost function for autonomous driving,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Differentiable integrated motion prediction and planning with learnable cost function for autonomous driving,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:37.809300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:36.598662Z digest=sha256:2b6f410110ab47048087154a5eb46d3927435b3908e2615d74ceca22953e8f94

Observation 1bbfc78a-f87f-4e42-a868-01890a07cac1 · outbound

This paper cites Stochastic trajectory prediction via motion indeterminacy diffusion,.

Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning Stochastic trajectory prediction via motion indeterminacy diffusion,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:38:37.526520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:38:36.716242Z digest=sha256:5adbc24d74f3e0b0ec971e41ed901bf9794c8989d5399d92bead9544a25cf305

Pith citing papers

Observation 9477e58b-7f42-474b-930f-950d54d316e3 · inbound

Generative Active Learning for Long-tail Trajectory Prediction via Controllable Diffusion Model cites this paper.

Generative Active Learning for Long-tail Trajectory Prediction via Controllable Diffusion Model Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T11:34:38.462448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:34:38.462448Z digest=sha256:ad0b5959d6581b1e2b66944775f78696341ad8da420ca92f8f76b6b87e5332a4

Observation 5e59496e-71a2-4290-a56d-2d6428f439fa · inbound

Multimodal embodiment-aware navigation transformer cites this paper.

Multimodal embodiment-aware navigation transformer Non-differentiable Reward Optimization for Diffusion-based Autonomous Motion Planning

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-10T02:38:17.344445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T02:37:50.624886Z digest=sha256:9edf188b2bee3bb10a8164bd4f22ccc2eff0dc0198b9ad2a437601ccf6986b91