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Paper Citation Record · LEDGER

Model Tensor Planning

As of 17 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2505.01059.

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

pith.paper-citation-record.v1
2505.01059 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:35:26.941807Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:59:53.079090Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T10:59:53.362326Z

Reference resolution

49 of 49 outbound references displayed

  • verified exact1
  • verified fuzzy24
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation db723f84-6fc8-4c22-99c8-47d74c841c67 · outbound

This paper cites A method of bivariate interpolation and smooth surface fitting based on local procedures.

Model Tensor Planning A method of bivariate interpolation and smooth surface fitting based on local procedures

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.678564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.695414Z digest=sha256:333367e15f7e2590a3f3fe237c3cce856359ed06f62c552eb7d63294a3d15079

Observation f51b01a5-4ab7-4c58-8369-44e2a68b12b5 · outbound

This paper cites Real-Time Whole-Body Control of Legged Robots with Model-Predictive Path Integral Control.

Model Tensor Planning Real-Time Whole-Body Control of Legged Robots with Model-Predictive Path Integral Control

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.701619Z digest=sha256:f6cdb6968564a139ab0be00fbf87453045e0e919cfdd2a4dc8c3fee64c7c71e9

Observation 4080a07c-4811-418d-8b2d-41d1925a37e0 · outbound

This paper cites Learning dexterous in-hand manipulation.

Model Tensor Planning Learning dexterous in-hand manipulation

Reference 3

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.707643Z digest=sha256:28ab9d384afee34e757df605e58fe6244881164d6ee29f3cad2a95173d11f85a

Observation 7f49d56e-5c29-4f47-9d24-050cb0293cb3 · outbound

This paper cites Storm: An integrated framework for fast joint-space model-predictive control for reactive manipulation.

Model Tensor Planning Storm: An integrated framework for fast joint-space model-predictive control for reactive manipulation

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.658171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.714332Z digest=sha256:442c60fa52abed9293023d13ceb42fb90bee5b4038dc882b63de538657ed7eb6

Observation af0d06c1-1fa6-4121-a6b9-66bd76e31b6b · outbound

This paper cites Massively parallelizing the rrt and the rrt.

Model Tensor Planning Massively parallelizing the rrt and the rrt

Reference 5

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raw_fallback, observed 2026-08-16T04:35:27.644687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.721285Z digest=sha256:5ad852766439a7a80991d4bf3f52c4a43f1b480797f7c67842fafaa01e58eb6a

Observation c89d6b18-81f0-450d-9942-89ff3531f7c2 · outbound

This paper cites JAX : composable transformations of P ython+ N um P y programs, 2018.

Model Tensor Planning JAX : composable transformations of P ython+ N um P y programs, 2018

Reference 6

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raw_fallback, observed 2026-08-16T04:35:27.631623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.727545Z digest=sha256:badce5be6ddacee40a762cfe7635fea773c923eaa4a270856c8ca08e7fbf1fc6

Observation a2e06d01-a228-41c5-86a8-f7c967743e95 · outbound

This paper cites Motion Planning Diffusion: Learning and Adapting Robot Motion Planning with Diffusion Models.

Model Tensor Planning Motion Planning Diffusion: Learning and Adapting Robot Motion Planning with Diffusion Models

Reference 7

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no resolver link, observed 2026-08-16T04:35:26.733268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.733268Z digest=sha256:27b1f4222e1963b22a7ab3ac1b7b7e073821f1f7bf7ddf589f548b552f89f63e

Observation 4ddee45c-b72c-48a5-81a4-e96b98efe53d · outbound

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

Model Tensor Planning Motion planning diffusion: Learning and planning of robot motions with diffusion models

Reference 8

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no resolver link, observed 2026-08-16T04:35:26.739260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.739260Z digest=sha256:1658f3534783985a01b534ac4650011d5bcbe95c14c77f93adf77bedd7133a32

Observation 8173d9e9-cf51-4864-8a2b-2e79e0b46991 · outbound

This paper cites Diffusion policy: Visuomotor policy learning via action diffusion.

Model Tensor Planning Diffusion policy: Visuomotor policy learning via action diffusion

Reference 9

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no resolver link, observed 2026-08-16T04:35:26.743682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.743682Z digest=sha256:b77d977f91a62d9144ea5ef7671124f156ca0f14f36f512957d827a6b6558711

Observation 7238b0e5-45e3-4447-a86b-f80eba092be8 · outbound

This paper cites A tutorial on the cross-entropy method.

Model Tensor Planning A tutorial on the cross-entropy method

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.603249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.750632Z digest=sha256:0fb5ff665357e9c99ea5319dc0ce643cdc365fabcac66101b06b1584b9f14d70

Observation fa1e4b72-ebe8-40ad-921f-51b0104683aa · outbound

This paper cites Package for calculating with b-splines.

Model Tensor Planning Package for calculating with b-splines

Reference 11

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verified exact
doi, observed 2026-08-16T04:35:26.977801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.756599Z digest=sha256:c80bc918fbfec295846ae678b4d8a7df21c692e117e98962238cc8d7d6daab44

Observation 1af1b952-8ce5-4594-a9ba-6dbbed71e944 · outbound

This paper cites The CMA Evolution Strategy: A Tutorial.

Model Tensor Planning The CMA Evolution Strategy: A Tutorial

Reference 12

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-16T04:35:26.761508Z digest=sha256:6dbbc9bf7b7c0fcea99fbe6163ff5c0aa901018b50d33485c11082bf047fb898

Observation d172849a-c989-467a-bf3c-e3dc4401e66a · outbound

This paper cites Denoising diffusion probabilistic models.

Model Tensor Planning Denoising diffusion probabilistic models

Reference 13

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source=arxiv_source observed=2026-08-16T04:35:26.767176Z digest=sha256:e4be1c2912070e5767f51eb80e0f47a2adef65efa35fb00ae56cb016b5c256f9

Observation d9021ec0-f17a-4d74-923c-c041af70f076 · outbound

This paper cites Predictive Sampling: Real-time Behaviour Synthesis with MuJoCo.

Model Tensor Planning Predictive Sampling: Real-time Behaviour Synthesis with MuJoCo

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.771805Z digest=sha256:e35a7b1e121e2326f076842ac3cf1723079bb8570c57d733242a160df36f5ab5

Observation 3f27b575-5868-4aff-b275-dc7b58c7474a · outbound

This paper cites prrtc: Gpu-parallel rrt-connect for fast, consistent, and low-cost motion planning.

Model Tensor Planning prrtc: Gpu-parallel rrt-connect for fast, consistent, and low-cost motion planning

Reference 15

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no resolver link, observed 2026-08-16T04:35:26.776664Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.776664Z digest=sha256:7969557702111c605f69b16c24a5a7facdac5ad84bd40801ce27dd8cda474895

Observation f9c20458-f29e-43ed-b252-9118fe6cc11b · outbound

This paper cites DiffusionSeeder: Seeding Motion Optimization with Diffusion for Rapid Motion Planning.

Model Tensor Planning DiffusionSeeder: Seeding Motion Optimization with Diffusion for Rapid Motion Planning

Reference 16

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no resolver link, observed 2026-08-16T04:35:26.782127Z

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source=arxiv_source observed=2026-08-16T04:35:26.782127Z digest=sha256:17d9796c20b10e510791fbc1a631d25c3313a49bf3f0a9e76e2a3c31180ee4dc

Observation 2e203545-d94c-457c-8dca-feb568103134 · outbound

This paper cites Vp-sto: Via-point-based stochastic trajectory optimization for reactive robot behavior.

Model Tensor Planning Vp-sto: Via-point-based stochastic trajectory optimization for reactive robot behavior

Reference 17

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raw_fallback, observed 2026-08-16T04:35:27.582794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.788064Z digest=sha256:45ac4979e64c8085c0ae59d86b327fbcdbbe685196b742f249de2a920236c7e0

Observation 6e8de761-688e-42ea-b125-4a587be171ef · outbound

This paper cites Rrt-connect: An efficient approach to single-query path planning.

Model Tensor Planning Rrt-connect: An efficient approach to single-query path planning

Reference 18

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raw_fallback, observed 2026-08-16T04:35:27.568823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.794253Z digest=sha256:d619e7f1b815771622d6f1af976c7a094ba9f5c7fb01edc1879a09c1f02cb9dd

Observation ea7bf044-63b0-470a-aa75-8cbb353a8d27 · outbound

This paper cites Hydrax: Sampling-based model predictive control on gpu with jax and mujoco mjx, 2024.

Model Tensor Planning Hydrax: Sampling-based model predictive control on gpu with jax and mujoco mjx, 2024

Reference 19

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raw_fallback, observed 2026-08-16T04:35:27.555932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.799570Z digest=sha256:ed55898261265db718b8c86e383560341545c96379833bc6fd7660abe28b8768

Observation 694fd673-af14-4e41-a824-3f3a3836677b · outbound

This paper cites evosax: Jax-based evolution strategies.

Model Tensor Planning evosax: Jax-based evolution strategies

Reference 20

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raw_fallback, observed 2026-08-16T04:35:27.544104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.805490Z digest=sha256:97d26148e855e6e1e35d489c3045d34cc6d900a8079744490ef2a71f78cecfa9

Observation 92f19877-a778-4c14-ae06-3696e31d657d · outbound

This paper cites Gpu parallelization of policy iteration rrt.

Model Tensor Planning Gpu parallelization of policy iteration rrt

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.530866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.810887Z digest=sha256:cda331123232d99d6ed2ab41dc1a12df8e77847768e38c224560ec987f9c0407

Observation 042a4812-18ae-4d92-9f23-0e5bd58f9a82 · outbound

This paper cites Accelerating motion planning via optimal transport.

Model Tensor Planning Accelerating motion planning via optimal transport

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.518827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.816216Z digest=sha256:40ad2dd855df0d0c49132d23efd2ed33a612f06f383aa78b02627e848cd8361f

Observation 5ac97b3e-ad2b-4b59-a271-0e68f11ccbe0 · outbound

This paper cites Global Tensor Motion Planning.

Model Tensor Planning Global Tensor Motion Planning

Reference 23

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.820575Z digest=sha256:b6cfa648bdc5aab70037fb38f53be4d6fe0c5f357ed172f3c4f0e87cb1a77435

Observation 70399163-ba77-4283-b398-f610dcf04ec5 · outbound

This paper cites DROP: Dexterous Reorientation via Online Planning.

Model Tensor Planning DROP: Dexterous Reorientation via Online Planning

Reference 24

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no resolver link, observed 2026-08-16T04:35:26.826254Z

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source=arxiv_source observed=2026-08-16T04:35:26.826254Z digest=sha256:712a46b1952ec9a68c3d24b3cfc3d745863a6bc0d39b9a5e5b2923911f4995d6

Observation 9611f0c6-225b-4e9a-8d95-ddd296bf494d · outbound

This paper cites Stochastic mpc with offline uncertainty sampling.

Model Tensor Planning Stochastic mpc with offline uncertainty sampling

Reference 25

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.833863Z digest=sha256:fc36b7cfda83887dcb6b8ba4a8510c996e6f5021a4b8479a3b45fe47c109c339

Observation 9068ed63-7fd2-495e-a4c7-a74b763e7d73 · outbound

This paper cites Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning.

Model Tensor Planning Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning

Reference 26

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.838754Z digest=sha256:f9d5e785be28cbfd5cb8bd419db75812e2674f5b03e150342972e0d7210c3ccd

Observation c51d1f59-3c9d-4fb5-83b8-6346a3284d1c · outbound

This paper cites Model predictive control: Recent developments and future promise.

Model Tensor Planning Model predictive control: Recent developments and future promise

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.499582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.843737Z digest=sha256:b251bde78737b7695da8b3dc336c7b4bf814549fd20bed537233767aee136078

Observation 3054d852-6fbf-4b46-924a-73b910d09690 · outbound

This paper cites FlowMP: Learning Motion Fields for Robot Planning with Conditional Flow Matching.

Model Tensor Planning FlowMP: Learning Motion Fields for Robot Planning with Conditional Flow Matching

Reference 28

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no resolver link, observed 2026-08-16T04:35:26.848308Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.848308Z digest=sha256:dda4f33027fd04b4be4776f5c0f7d127b082f470517322e8d488df827ed09121

Observation 7f84d4c7-24a8-422f-b5dc-634c54bcf6ee · outbound

This paper cites Gpu-based parallel collision detection for fast motion planning.

Model Tensor Planning Gpu-based parallel collision detection for fast motion planning

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.487401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.852756Z digest=sha256:3f6bdcb3b8345212fa2a636fd6250d0f6cbd7f60373e1c95f036d04dba9e641c

Observation 0ab53c59-2809-4383-9917-9489f9ab976f · outbound

This paper cites Kino-pax: Highly parallel kinodynamic sampling-based planner.

Model Tensor Planning Kino-pax: Highly parallel kinodynamic sampling-based planner

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.473792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.857380Z digest=sha256:35caf9bc717b83ce2a27b68922d52f01d7fe5f4300b7e9714992881148e4a30d

Observation 692bfd5c-27cb-413e-8e57-2fb6adba5321 · outbound

This paper cites Sampling-based model predictive control leveraging parallelizable physics simulations.

Model Tensor Planning Sampling-based model predictive control leveraging parallelizable physics simulations

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.460498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.862212Z digest=sha256:59e479a06de6f13929eac0981b6164fa29aeb0d1214ccb79990f7a7033395719

Observation 9e0c7202-561e-4aff-bf24-efccc897d0d3 · outbound

This paper cites Sample-efficient cross-entropy method for real-time planning.

Model Tensor Planning Sample-efficient cross-entropy method for real-time planning

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.448539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.866873Z digest=sha256:8171f8fb3ad8fca08721eb7f0a33783be3a88e091efb0fc8cb16800ffe25ee2d

Observation 3328cef8-3661-4dce-9969-9e6034e6c761 · outbound

This paper cites Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

Model Tensor Planning Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Reference 33

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no resolver link, observed 2026-08-16T04:35:26.871139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.871139Z digest=sha256:221c531f39898cc8154d616b2850f2ce4f1ac8f47e8c143497b846325fcf503e

Observation 1dd5f542-93b6-4d96-a36c-7d9477d16320 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Model Tensor Planning Proximal Policy Optimization Algorithms

Reference 34

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no resolver link, observed 2026-08-16T04:35:26.875514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.875514Z digest=sha256:afc966ce0df40e463b1375441e03caab24a282d0f722b090ed6d52da08f4ed76

Observation 2159d4db-c1a1-4cbe-9522-03592998856c · outbound

This paper cites Curobo: Parallelized collision-free robot motion generation.

Model Tensor Planning Curobo: Parallelized collision-free robot motion generation

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.434316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.880148Z digest=sha256:81b4c649960e22dc500d1697346d3cf8c5c88a5b9491bd382a5b9c5134c9531b

Observation 1c7fd68d-b01f-4d59-8939-ae7be0e661b2 · outbound

This paper cites Motions in microseconds via vectorized sampling-based planning.

Model Tensor Planning Motions in microseconds via vectorized sampling-based planning

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.419747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-16T04:35:26.884606Z digest=sha256:fabf68bfc6554bb6a23a12ccc333ed687576161ab6356b8ad8119c1cc7446002

Observation f4612abc-f154-481f-8304-e4ced7aead3a · outbound

This paper cites Mujoco: A physics engine for model-based control.

Model Tensor Planning Mujoco: A physics engine for model-based control

Reference 37

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source=arxiv_source observed=2026-08-16T04:35:26.888690Z digest=sha256:1942f4bc8bd7081e9acc74cb6e53d9fc6bd377b4ce43ae8f4c187197ab1e2c83

Observation 4032a085-1ceb-4e4e-a7bb-ce72cf7a82c2 · outbound

This paper cites Gymnasium: A Standard Interface for Reinforcement Learning Environments.

Model Tensor Planning Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:35:26.893733Z digest=sha256:141001659a0b3a02526f144cfc3fef38514d423f634f0ded20921c7de2aaddd7

Observation 1d5a3160-ac6a-47c8-ac65-b51d1334dcde · outbound

This paper cites Learning implicit priors for motion optimization.

Model Tensor Planning Learning implicit priors for motion optimization

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.395395Z

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source=arxiv_source observed=2026-08-16T04:35:26.898972Z digest=sha256:0d491b8b5899078d0d36bf0cb0d7c4ef84b490695910ce4a0fee58213bca1dec

Observation 23c59880-1a6d-4942-90ac-c1ffe25a3a99 · outbound

This paper cites Mppi-generic: A cuda library for stochastic optimization.

Model Tensor Planning Mppi-generic: A cuda library for stochastic optimization

Reference 40

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no resolver link, observed 2026-08-16T04:35:26.903263Z

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source=arxiv_source observed=2026-08-16T04:35:26.903263Z digest=sha256:1c22c9442464e347a6ba03e468e9ae3d1c61fc2972b122c60b199cc0a5b378e5

Observation d609f2a7-64e6-45ed-9521-73349a5eebf6 · outbound

This paper cites Inferring smooth control: Monte carlo posterior policy iteration with gaussian processes.

Model Tensor Planning Inferring smooth control: Monte carlo posterior policy iteration with gaussian processes

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.381782Z

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source=arxiv_source observed=2026-08-16T04:35:26.908009Z digest=sha256:9273a19290390bad72aec76b65514a6b4f9eb4ac0df3ea84e1acd1d8e3116230

Observation b9da26b1-4237-4558-a780-7ae3f914bb66 · outbound

This paper cites Natural evolution strategies.

Model Tensor Planning Natural evolution strategies

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.365648Z

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source=arxiv_source observed=2026-08-16T04:35:26.912106Z digest=sha256:612e6944513bce77028541ca0e64af77f4c7f9f17e23b5b8ea7ac1a8bdc324c4

Observation 901efdf3-01b5-4dd7-b014-741c49a44d47 · outbound

This paper cites Model predictive path integral control: From theory to parallel computation.

Model Tensor Planning Model predictive path integral control: From theory to parallel computation

Reference 43

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unresolved
no resolver link, observed 2026-08-16T04:35:26.916243Z

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source=arxiv_source observed=2026-08-16T04:35:26.916243Z digest=sha256:1ba2a30d0f3b5d731cc444b2058b82a729dab709ac8035e187a9c2f6d3c95642

Observation d9e3a182-19b9-4dd2-8da1-8acafe3fc029 · outbound

This paper cites Full-Order Sampling-Based MPC for Torque-Level Locomotion Control via Diffusion-Style Annealing.

Model Tensor Planning Full-Order Sampling-Based MPC for Torque-Level Locomotion Control via Diffusion-Style Annealing

Reference 44

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source=arxiv_source observed=2026-08-16T04:35:26.920443Z digest=sha256:a898dd54547a186acb990e323fd62408dab769ad34632c1c48eebbfd53724fb0

Observation ba758f03-5d3f-41b2-8350-17f9e6de07eb · outbound

This paper cites Covo-mpc: Theoretical analysis of sampling-based mpc and optimal covariance design.

Model Tensor Planning Covo-mpc: Theoretical analysis of sampling-based mpc and optimal covariance design

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.335253Z

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source=arxiv_source observed=2026-08-16T04:35:26.925515Z digest=sha256:645c8d9a00b157de394b795891b6563c27e1709119a877c9750ad19867c5b0b9

Observation d12fbcd7-d7f6-4f5c-b751-eaa94946d6f1 · outbound

This paper cites Diffusion Models are Evolutionary Algorithms.

Model Tensor Planning Diffusion Models are Evolutionary Algorithms

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-16T04:35:26.929705Z

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source=arxiv_source observed=2026-08-16T04:35:26.929705Z digest=sha256:1b975772daa266174c743ce33a5fea62525410ed32942fbdd7466600fbdc25e8

Observation f3aadc49-e9d2-40ce-88bd-5f2d53a25b97 · outbound

This paper cites A simple decentralized cross-entropy method.

Model Tensor Planning A simple decentralized cross-entropy method

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.322126Z

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source=arxiv_source observed=2026-08-16T04:35:26.933701Z digest=sha256:13de436661870e4693a1fd3797ae78d744a579d3f3810129ff3d1425606b6924

Observation 1243760e-f7a5-455b-ab89-f3027bfd7783 · outbound

This paper cites Chomp: Covariant hamiltonian optimization for motion planning.

Model Tensor Planning Chomp: Covariant hamiltonian optimization for motion planning

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T04:35:27.307457Z

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source=arxiv_source observed=2026-08-16T04:35:26.937972Z digest=sha256:20b194b709a4d0a963902f6b22087bfba4ca3928eb2133c09d92e1370d899870

Observation decea9a2-d66f-4e93-a25b-4cbc983f1c84 · outbound

This paper cites write newline.

Model Tensor Planning write newline

Reference 49

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unresolved
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source=arxiv_source observed=2026-08-16T04:35:26.941807Z digest=sha256:624d36de9c8d854c518761a46153523702f46a89ed47a7295ecc13f87e510690

Pith citing papers

Observation 5a0b58f8-4ce7-4dbe-8cb7-f12014c7a62d · inbound

MOSAIC: Skill-Centric Manipulation Planning with Physics Simulation cites this paper.

MOSAIC: Skill-Centric Manipulation Planning with Physics Simulation Model Tensor Planning

Reference 12

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verified exact
local_arxiv, observed 2026-08-16T10:59:53.365896Z

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source=pdf_text observed=2026-08-16T10:59:53.079090Z digest=sha256:ff479af856190583e5232549d6fed5478dff2c640af0088e1c9981dab3149ba9