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Paper Citation Record · LEDGER

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning

As of 16 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2411.17293.

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

pith.paper-citation-record.v1
2411.17293 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:21:45.545914Z

measured 35 of 35 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

  • verified exact1
  • verified fuzzy27
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b41af1a-67a6-4fb7-960c-013f61f3e56a · outbound

This paper cites Global overview of imitation learning, 2018.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Global overview of imitation learning, 2018

Reference 1

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Source-reported events for the cited work

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

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Observation 6417aa10-4b46-4dbe-acb8-e90aa3ccdffe · outbound

This paper cites Leveraging neural net- works to guide path planning: Improving dataset generation and planning efficiency.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Leveraging neural net- works to guide path planning: Improving dataset generation and planning efficiency

Reference 2

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raw_fallback, observed 2026-08-12T12:21:46.131094Z

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

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Observation 3eaeeb7c-25bf-4a08-aceb-14f2bbcf29ac · outbound

This paper cites Modeling human driving behavior through generative adversarial imitation learning.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Modeling human driving behavior through generative adversarial imitation learning

Reference 3

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raw_fallback, observed 2026-08-12T12:21:46.114328Z

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.

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Observation f2cadfd9-b0fe-4a37-a1fe-a4a7556be83b · outbound

This paper cites Ex- trapolating beyond suboptimal demonstrations via inverse reinforcement learning from observations.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Ex- trapolating beyond suboptimal demonstrations via inverse reinforcement learning from observations

Reference 4

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raw_fallback, observed 2026-08-12T12:21:46.097812Z

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.

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Observation 251f8149-6510-4c68-9c63-fffeee7fe8ed · outbound

This paper cites Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Learning to Plan in High Dimensions via Neural Exploration-Exploitation Trees

Reference 5

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T12:21:45.397683Z digest=sha256:894ca01a2c2549e6a3e6b30a057ac789cf0f98b4ebd2dfde367c63e490a78373

Observation a45b8ca0-6082-4cd0-ab60-2b056403d903 · outbound

This paper cites Deci- sion transformer: Reinforcement learning via sequence modeling.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Deci- sion transformer: Reinforcement learning via sequence modeling

Reference 6

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Source-reported events for the cited work

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

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Observation 8715b110-0146-41ab-8f5a-334d266479c4 · outbound

This paper cites RL-RRT: kinodynamic motion planning via learning reach- ability estimators from rl policies.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning RL-RRT: kinodynamic motion planning via learning reach- ability estimators from rl policies

Reference 7

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T12:21:45.408502Z digest=sha256:ada33aa42624bfadee22a4e1c247e230df9e3c848c87f18d6bca0ca3d8640894

Observation 1e9fc3ce-5fa8-42e1-b016-11ef88edf1a3 · outbound

This paper cites Deep RRT.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Deep RRT

Reference 8

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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.

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Observation a68d3a30-39ab-4cc4-9daf-0462402b7ab5 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

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Observation edaef04c-1abf-45d4-afcc-611f0cbf478b · outbound

This paper cites Survey of imitation learning for robotic manipulation.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Survey of imitation learning for robotic manipulation

Reference 10

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raw_fallback, observed 2026-08-12T12:21:46.030270Z

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.

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Observation a78e5516-faa2-409f-bc7a-44565f527cd0 · outbound

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

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Informed RRT*: optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic

Reference 11

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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.

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Observation 21105e5d-12ea-4b57-a59a-54ea068b1162 · outbound

This paper cites Batch Informed Trees (BIT): sampling-based optimal planning via the heuristically guided search of implicit random geometric graphs.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Batch Informed Trees (BIT): sampling-based optimal planning via the heuristically guided search of implicit random geometric graphs

Reference 12

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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=2026-08-12T12:21:45.432428Z digest=sha256:229dbab1492901f95cd9db679f38533a0d768435deafa17535249ecb43d57481

Observation cf99bccb-5d93-4832-aad5-c29d6a01a19b · outbound

This paper cites Generative adversarial imitation learn- ing.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Generative adversarial imitation learn- ing

Reference 13

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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.

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Observation 2f0a89ba-1d32-47a6-a454-16ad131b7af2 · outbound

This paper cites Learning sampling distri- butions for robot motion planning.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Learning sampling distri- butions for robot motion planning

Reference 14

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raw_fallback, observed 2026-08-12T12:21:45.964584Z

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.

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Observation bf39371d-6747-404b-98eb-0684dac57173 · outbound

This paper cites RRT*-smart: rapid convergence implementation of rrt* towards optimal solution.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning RRT*-smart: rapid convergence implementation of rrt* towards optimal solution

Reference 15

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raw_fallback, observed 2026-08-12T12:21:45.947813Z

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.

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Observation d5b8d67c-6cf8-431d-86c4-5c7eb4662440 · outbound

This paper cites Perceiver IO: A General Architecture for Structured Inputs & Outputs.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Perceiver IO: A General Architecture for Structured Inputs & Outputs

Reference 16

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e252b6b3-0548-4c3e-85ea-3abd5ac9d6e2 · outbound

This paper cites Perceiver: General perception with iterative attention.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Perceiver: General perception with iterative attention

Reference 17

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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.

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Observation 534ece0f-aec3-4b8d-a85c-48d53111f588 · outbound

This paper cites Optimal bidirectional rapidly- exploring random trees.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Optimal bidirectional rapidly- exploring random trees

Reference 18

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Source-reported events for the cited work

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

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Observation 50e903ce-a8b9-43c1-8708-07512b44ec43 · outbound

This paper cites Sampling-based algorithms for op- timal motion planning.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Sampling-based algorithms for op- timal motion planning

Reference 19

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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.

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Observation 36642d52-bdc1-4b91-bea1-820194f59086 · outbound

This paper cites Probabilistic roadmaps for path planning in high-dimensional configura- tion spaces.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Probabilistic roadmaps for path planning in high-dimensional configura- tion spaces

Reference 20

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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.

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Observation 8ef553ed-566c-491a-8268-618291a9df42 · outbound

This paper cites Graph Neural Networks for Motion Planning.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Graph Neural Networks for Motion Planning

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:21:45.476867Z digest=sha256:453b3f33c341f9e9e95ccd15919f36b11cee9f41110ba1d4bd7d5de91d96b51f

Observation 1fae8c11-74ce-48dc-b459-06db1bd6e737 · outbound

This paper cites LEGO: Leveraging experience in roadmap generation for sampling-based planning.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning LEGO: Leveraging experience in roadmap generation for sampling-based planning

Reference 22

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raw_fallback, observed 2026-08-12T12:21:45.865911Z

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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=2026-08-12T12:21:45.481939Z digest=sha256:db44feebf0e795bb57a080ea7015d26c52fb14cd6e8f78430a4b4315fac38469

Observation ef36bbb2-d5ae-4dc8-a53a-b972741f20de · outbound

This paper cites Randomized kinodynamic plan- ning.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Randomized kinodynamic plan- ning

Reference 23

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raw_fallback, observed 2026-08-12T12:21:45.849022Z

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=2026-08-12T12:21:45.487594Z digest=sha256:b70b6bd65929019e5f77683bd8b54af572ab937747099f959bbe0d917579de82

Observation 1ae3e3dd-b7c6-4520-93e8-5ae744f66990 · outbound

This paper cites Self-imitation learn- ing by planning.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Self-imitation learn- ing by planning

Reference 24

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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=2026-08-12T12:21:45.492451Z digest=sha256:54d3997c57345a6926597c49dce79ea91039bf230b7a33ba3d4d4fcfeeeab52a

Observation 47322c77-d1cf-46d5-92d0-325e24977bb1 · outbound

This paper cites NR-RRT: Neural Risk-Aware Near-Optimal Path Planning in Uncertain Nonconvex Environments.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning NR-RRT: Neural Risk-Aware Near-Optimal Path Planning in Uncertain Nonconvex Environments

Reference 25

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local_arxiv, observed 2026-08-12T12:21:45.625344Z

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

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Observation 082fb378-f8a9-4f21-aea2-2fc2b2bb48c3 · outbound

This paper cites Self-imitation learning.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Self-imitation learning

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-12T12:21:45.815167Z

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=2026-08-12T12:21:45.501986Z digest=sha256:cff60c28f2b837c1f1104b262e7f1f658f356891482875dde6fbb88c100a46f7

Observation c7419522-eff4-44c1-bb74-d45d61e53695 · outbound

This paper cites Motion planning networks.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Motion planning networks

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:21:45.799709Z

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=2026-08-12T12:21:45.506697Z digest=sha256:df5113f561a433c1d3c780601f46d46c43c70b73b2961dcacce953ca29b83942

Observation ef801702-b70b-4f23-ae97-33d8d69a7a54 · outbound

This paper cites SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:21:45.511573Z digest=sha256:53e2b40f8a8fa9922e416e2331f285191ec0f610bc1c774bc10b9a39ea4ab1d1

Observation 88ec1947-fe8d-437c-8914-b1db968781a2 · outbound

This paper cites CBAGAN-RRT: convolutional block attention generative adversarial network for sampling-based path planning, 2023.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning CBAGAN-RRT: convolutional block attention generative adversarial network for sampling-based path planning, 2023

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-12T12:21:45.783991Z

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=2026-08-12T12:21:45.516800Z digest=sha256:5e395de9cec2b3ae5e01bc7b43cac8aef291c2ab3c3e04bbe8084d63225b9abc

Observation 2d364d40-2b93-460b-b7b4-ccc1579a02a5 · outbound

This paper cites Learning obstacle representa- tions for neural motion planning.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Learning obstacle representa- tions for neural motion planning

Reference 30

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raw_fallback, observed 2026-08-12T12:21:45.767095Z

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=2026-08-12T12:21:45.521442Z digest=sha256:b52b78b7a28aa647509ad947fd77218df310ebe60c6f7b39339653d13205f3ff

Observation 0d30a0cb-3d35-48ca-834f-364e18674053 · outbound

This paper cites Attention is all you need.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Attention is all you need

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:21:45.526245Z digest=sha256:7e656d5b9c90342b0e78ebdef2b35d262e83e3a9a4648245cffcfe69cec631f2

Observation 9a3f5b01-dddc-410e-8053-b248053877c9 · outbound

This paper cites Robust adversarial imitation learning via adaptively-selected demonstrations.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Robust adversarial imitation learning via adaptively-selected demonstrations

Reference 32

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raw_fallback, observed 2026-08-12T12:21:45.740479Z

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=2026-08-12T12:21:45.531225Z digest=sha256:73a276f2f4043953896cb680384b158c03f9e307c73b0ae8dd3d04f9d95beffd

Observation 8a4f2104-3f85-4391-a97d-294f2533dec8 · outbound

This paper cites Imitation learning from imperfect demonstration.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Imitation learning from imperfect demonstration

Reference 33

Resolution
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raw_fallback, observed 2026-08-12T12:21:45.723974Z

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=2026-08-12T12:21:45.536138Z digest=sha256:85ca27c88795251044a58762265b2e1422eb77f8ca53deff0dd04c833496f679

Observation 00c30d85-50b2-4c13-9746-9d987ee2ee24 · outbound

This paper cites Query-Efficient Imitation Learning for End-to-End Autonomous Driving.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Query-Efficient Imitation Learning for End-to-End Autonomous Driving

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:21:45.540914Z digest=sha256:54d21e5b7783891dddf654d07673c71b9eef0a38033999f524affdbb3a9068bb

Observation 1301760e-99fa-4d7a-bcfb-f51424d2e0c0 · outbound

This paper cites Learning-based motion planning in dynamic environments using gnns and temporal encoding.

SIL-RRT*: Learning Sampling Distribution through Self Imitation Learning Learning-based motion planning in dynamic environments using gnns and temporal encoding

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:21:45.708306Z

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=2026-08-12T12:21:45.545914Z digest=sha256:63a41fcb578693223dc0eaf7d07dbae5bf4cdfd49555c9e5c9f7a2b743222f61

Pith citing papers

No inbound Pith citation observations are available.