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Paper Citation Record · LEDGER

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning

As of 15 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 1 inbound Pith citation observation for arXiv:2606.06041.

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

pith.paper-citation-record.v1
2606.06041 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T01:38:04.259088Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T05:27:36.041773Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

  • verified exact3
  • verified fuzzy0
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 661bb16c-bacd-4457-aa6c-34fa077dc70a · outbound

This paper cites Artificial intelligence, machine learning and deep learning in advanced robotics, a review.Cognitive Robotics, 3:54–70, 2023.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Artificial intelligence, machine learning and deep learning in advanced robotics, a review.Cognitive Robotics, 3:54–70, 2023

Reference 1

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:d81f64f2a9e4cf4fb8129c9599955ed94f0355b587fa3d88fa3e62b739e3da64

Observation dc67f07b-525a-4e86-8880-27f0bbbc1336 · outbound

This paper cites An open-source multi-goal rein- forcement learning environment for robotic manipulation with pybullet.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning An open-source multi-goal rein- forcement learning environment for robotic manipulation with pybullet

Reference 2

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:82790d54a9a072aaaf70fc2cde00755ea90eff0b05788f7ffd7ea28c5797b333

Observation e35c6bd5-3cc1-4237-8e7c-a142d17fd7cc · outbound

This paper cites Curious exploration via structured world models yields zero-shot object manipulation.Advances in Neural Information Processing Systems, 35:24170–24183, 2022.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Curious exploration via structured world models yields zero-shot object manipulation.Advances in Neural Information Processing Systems, 35:24170–24183, 2022

Reference 3

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no resolver link, observed 2026-06-28T01:38:04.259088Z

Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:fd60511e53cd0e08fc5c3b0298df2906285f42f2c6c76c9ec2a9529dd4007072

Observation 34622532-7dd1-4d2d-bd9e-c725dfa0f528 · outbound

This paper cites Transfer learning in robotics: An upcoming breakthrough? a review of promises and challenges.The International Journal of Robotics Research, 44(3):465–485, 2025.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Transfer learning in robotics: An upcoming breakthrough? a review of promises and challenges.The International Journal of Robotics Research, 44(3):465–485, 2025

Reference 4

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Source-reported events for the cited work

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:a00fc2b148fa5d9fa7fb0d4fb931a908dc45e477a4b7dba690958f93bd342024

Observation cf5f20b4-d1ae-43f5-ba98-f4664e6e8ac3 · outbound

This paper cites Transfer learning in deep reinforcement learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(11):13344–13362, 2023.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Transfer learning in deep reinforcement learning: A survey.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(11):13344–13362, 2023

Reference 5

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:020e829dbf5a9f4d835011ed12e24b62062df33c00de2674792dfaa84c49dc6d

Observation 9d2082e8-95c0-478e-82df-1beaa497c45c · outbound

This paper cites Few-shot transfer learning for deep reinforcement learning on robotic manipulation tasks.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Few-shot transfer learning for deep reinforcement learning on robotic manipulation tasks

Reference 6

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:7b05693789b65319294a440e243f109a348d0374952b792197c74044bd60e3e5

Observation cb8a1150-1a1c-4e6a-a9c2-e1887fa979a7 · outbound

This paper cites Curious: intrinsically motivated modular multi-goal reinforce- ment learning.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Curious: intrinsically motivated modular multi-goal reinforce- ment learning

Reference 7

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:fbd3c7ea67d57486d2542f9cb5de7b305d60bd2534cc39628c9da4241eba456b

Observation bdd17a5d-646f-441d-ad75-4509e91e49bc · outbound

This paper cites Soft actor- critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Soft actor- critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 8

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:238c3fde1fa2a5c4daa47700a4ca2907a3e55c62b2909bce024e11d657bf1f26

Observation af1d6fda-43e3-4400-aab2-f7a6c6c887af · outbound

This paper cites Con- trolling overestimation bias with truncated mixture of continuous distributional quantile critics.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Con- trolling overestimation bias with truncated mixture of continuous distributional quantile critics

Reference 9

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:7be0694635673d87288a349f0893f1f3b6c301d3c417f692c2cde5ccfa4f6ad8

Observation 1e836c6c-083c-45d1-a599-e985d9969a3d · outbound

This paper cites Hindsight experience replay.Advances in neural information processing systems, 30, 2017.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Hindsight experience replay.Advances in neural information processing systems, 30, 2017

Reference 10

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:906200598ac50f41bde94f0e68c3a7ccd8254b15295b96fc833d08bfd665516d

Observation a4b1e11c-9ff2-4e8e-bdcc-2d33c359151e · outbound

This paper cites First return, then explore.Nature, 590(7847):580–586, 2021.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning First return, then explore.Nature, 590(7847):580–586, 2021

Reference 11

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:c056deb329af678b43dc234babebbeef5357e90982105895532a61a169e65b3e

Observation ab9c358a-73df-451a-b8ae-a69ab30c9d14 · outbound

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

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Reference 12

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verified exact
local_arxiv, observed 2026-07-02T13:06:58.906955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:6a0666095722c955f7a44080ac5e4884ab4640b429b3401bfe4864dc1b93910b

Observation 06b40be8-17b1-4908-84c9-c40c70f75109 · outbound

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

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Sample-efficient cross-entropy method for real-time planning

Reference 13

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:253187aa90b178bf45eef258150eb7504ecead4f8fa199cc6bc60fcf4c3b6a40

Observation 3ca50611-0e39-43c6-81f8-bab18b398eda · outbound

This paper cites Learning robotic manipulation policies from point clouds with conditional flow matching.Conference on Robot Learning (CoRL), 2024.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Learning robotic manipulation policies from point clouds with conditional flow matching.Conference on Robot Learning (CoRL), 2024

Reference 14

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source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:b94ff4ac92836a8e30fc15a3ef5487655d56d8b7a6afc7863c88183c2bad4710

Observation e6000e20-953a-441b-81c0-5e7b20d9a4d2 · outbound

This paper cites Neural MP: A Generalist Neural Motion Planner.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning Neural MP: A Generalist Neural Motion Planner

Reference 15

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arxiv_id, observed 2026-07-02T13:06:58.904133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:a7343db22c76867307edad42d5e3ec3ef8a8d24f614cd90440d299084cf83da0

Observation 9b094d1e-5b4e-4884-a644-901b2ed50db5 · outbound

This paper cites OpenAI Gym.

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning OpenAI Gym

Reference 16

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verified exact
local_arxiv, observed 2026-07-02T13:06:58.901504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-06-28T01:38:04.259088Z digest=sha256:7d414499f172fd6515c322c3a27e19acff42ef146f63f71765fa8be5db464cbe

Pith citing papers

Observation b5e6a082-468d-4d4c-925b-6b1207ff97e6 · inbound

Detector Confidence Signals Presence Rather Than Occlusion in Cluttered Manipulation cites this paper.

Detector Confidence Signals Presence Rather Than Occlusion in Cluttered Manipulation Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning

Reference 4

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source=arxiv_source observed=2026-08-02T05:27:36.041773Z digest=sha256:422f235fee4915c296d1c5134d44dc8b8b7aa7d087936d9c97a98e2f545fb373