Paper Citation Record · LEDGER

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search

As of 20 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2504.20969.

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

pith.paper-citation-record.v1
2504.20969 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:19:06.129625Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:12:22.493777Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T20:12:22.781506Z

Reference resolution

40 of 40 outbound references displayed

verified exact1
verified fuzzy29
unresolved9
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3ba6f9ec-06c5-446e-bddf-85e84c74eb82 · outbound

This paper cites Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking Protocols

Reference 1

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Source-reported events for the cited work

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Observation eec72e04-0fbe-4116-9170-21936f303611 · outbound

This paper cites Differentiable Discrete Elastic Rods for Real-Time Modeling of Deformable Linear Objects.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Differentiable Discrete Elastic Rods for Real-Time Modeling of Deformable Linear Objects

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T05:19:05.975880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95d84921-36f1-44af-82e9-cca02cfd291b · outbound

This paper cites Mechanical search: Multi-step retrieval of a target object occluded by clutter.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Mechanical search: Multi-step retrieval of a target object occluded by clutter

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.742611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1aa89b08-891b-469e-9ab5-9022738ea1bf · outbound

This paper cites The cluttered environment picking benchmark (cepb) for advanced warehouse automation: evaluating the perception, planning, control, and grasping of manipulation systems.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search The cluttered environment picking benchmark (cepb) for advanced warehouse automation: evaluating the perception, planning, control, and grasping of manipulation systems

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.730713Z

Source-reported events for the cited work

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Observation 727b60c5-4c96-419d-a061-ab1ff494d8b0 · outbound

This paper cites A planning framework for non-prehensile manipulation under clutter and uncertainty.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search A planning framework for non-prehensile manipulation under clutter and uncertainty

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.718984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e3176187-cf08-4809-b62d-fe56a92c6d7b · outbound

This paper cites Anygrasp: Robust and efficient grasp perception in spatial and temporal domains.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Anygrasp: Robust and efficient grasp perception in spatial and temporal domains

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T05:19:05.992924Z

Source-reported events for the cited work

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Observation 797ee09d-6df1-4cab-8915-ce71e7d7002d · outbound

This paper cites Prehensile and non-prehensile robotic pick-and- place of objects in clutter using deep reinforcement learning.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Prehensile and non-prehensile robotic pick-and- place of objects in clutter using deep reinforcement learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.699292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4ccfb68e-d77f-4312-864c-838ae328dcfe · outbound

This paper cites Hierar- chical task and motion planning in the now.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Hierar- chical task and motion planning in the now

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T05:19:06.000949Z

Source-reported events for the cited work

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Observation c26a09e3-19c1-4d1e-a008-d325aa47a0d5 · outbound

This paper cites Segment anything.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Segment anything

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T05:19:06.004867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bd284f3-1b67-4af0-973e-0b7d3d03de88 · outbound

This paper cites A review of robot learning for manipulation: Challenges, representations, and algorithms.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search A review of robot learning for manipulation: Challenges, representations, and algorithms

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.670063Z

Source-reported events for the cited work

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Observation d5a7b30f-0846-4eb1-986f-d3781798b1d7 · outbound

This paper cites Learning multi-step robotic manipulation policies from visual ob- servation of scene and q-value predictions of previous action.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Learning multi-step robotic manipulation policies from visual ob- servation of scene and q-value predictions of previous action

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.656701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ab16de22-5da7-4736-8d59-749681aaabee · outbound

This paper cites Visuomotor mechanical search: Learning to retrieve target objects in clutter.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Visuomotor mechanical search: Learning to retrieve target objects in clutter

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.642771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1ab1c12e-f5be-4bb6-80ee-ddea4385c4bf · outbound

This paper cites Semantic and geometric modeling with neural message passing in 3d scene graphs for hierarchical mechanical search.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Semantic and geometric modeling with neural message passing in 3d scene graphs for hierarchical mechanical search

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.630780Z

Source-reported events for the cited work

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Observation 9c9764f3-0907-4db8-bf16-3139452c2205 · outbound

This paper cites Hierarchical primi- tive composition: Simultaneous activation of skills with inconsistent action dimensions in multiple hierarchies.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Hierarchical primi- tive composition: Simultaneous activation of skills with inconsistent action dimensions in multiple hierarchies

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.618327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6e3eaebb-1415-4f6e-8a17-f1f146981299 · outbound

This paper cites Mpgnet: Learning move-push- grasping synergy for target-oriented grasping in occluded scenes.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Mpgnet: Learning move-push- grasping synergy for target-oriented grasping in occluded scenes

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.606439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d0fdcdbe-2e88-403f-924d-4b4e02ae5418 · outbound

This paper cites Towards practical multi-object manipulation using relational reinforcement learning.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Towards practical multi-object manipulation using relational reinforcement learning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.594875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8fe1148d-33dd-446c-8d5b-5519ea8e8314 · outbound

This paper cites Multi-Modal Fusion of In-Situ Video Data and Process Parameters for Online Forecasting of Cookie Drying Readiness.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Multi-Modal Fusion of In-Situ Video Data and Process Parameters for Online Forecasting of Cookie Drying Readiness

Reference 17

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Source-reported events for the cited work

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Observation c8c90a84-e4f5-4248-b806-3b7bbafae24a · outbound

This paper cites Synergistic task and motion planning with rein- forcement learning-based non-prehensile actions.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Synergistic task and motion planning with rein- forcement learning-based non-prehensile actions

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.582954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 18c29b1d-d07e-46ce-a8d7-ec690227080e · outbound

This paper cites Meta-learning-based domain generalization for cost-effective tool condition monitor- ing in ultrasonic metal welding.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Meta-learning-based domain generalization for cost-effective tool condition monitor- ing in ultrasonic metal welding

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.571387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0fc9e513-25e4-45d0-b9bf-d3be1b6463b4 · outbound

This paper cites Orbit: A unified simulation framework for interactive robot learning environments.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Orbit: A unified simulation framework for interactive robot learning environments

Reference 20

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Observation 431bdc13-6475-47c6-a771-eaa25799b344 · outbound

This paper cites Fast and resilient manipulation planning for object retrieval in cluttered and confined environments.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Fast and resilient manipulation planning for object retrieval in cluttered and confined environments

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.560294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7504834c-12c7-4c31-a846-6672d04a669e · outbound

This paper cites Aug- menting reinforcement learning with behavior primitives for diverse manipulation tasks.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Aug- menting reinforcement learning with behavior primitives for diverse manipulation tasks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.547397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6adffc21-ae20-4e69-b6e5-6ae0ba04d9eb · outbound

This paper cites Stable-baselines3: Reliable reinforcement learning imple- mentations.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Stable-baselines3: Reliable reinforcement learning imple- mentations

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.535482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c8d4d5f5-24c8-4a03-a8b9-156f5deb12e2 · outbound

This paper cites Task priority grasping and locomotion control of modular robot.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Task priority grasping and locomotion control of modular robot

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.522989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2ce007c6-7845-4e92-b009-32a634f09bef · outbound

This paper cites Exploring the limits of hierarchical world models in reinforcement learning.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Exploring the limits of hierarchical world models in reinforcement learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.511133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 268f81fb-cb07-41e9-a635-9f77ae403cb8 · outbound

This paper cites Proximal Policy Optimization Algorithms.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Proximal Policy Optimization Algorithms

Reference 26

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Source-reported events for the cited work

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Observation 4b21d077-0595-415e-9adb-d80f836fa444 · outbound

This paper cites Learn- ing to combine primitive skills: A step towards versa- tile robotic manipulation.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Learn- ing to combine primitive skills: A step towards versa- tile robotic manipulation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.498077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6785b121-71cd-49a5-a467-80be613b892f · outbound

This paper cites Selective object rearrangement in clutter.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Selective object rearrangement in clutter

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.485273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 51ffab55-a555-4770-8ebd-aed23459801c · outbound

This paper cites Multi-stage reinforcement learn- ing for non-prehensile manipulation.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Multi-stage reinforcement learn- ing for non-prehensile manipulation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.472500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 075170b7-e214-4d94-a9c6-167e8294d329 · outbound

This paper cites Hierarchical Visual Policy Learning for Long-Horizon Robot Manipulation in Densely Cluttered Scenes.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Hierarchical Visual Policy Learning for Long-Horizon Robot Manipulation in Densely Cluttered Scenes

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T05:19:06.089637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb9f41f5-86fb-4d56-a7c8-d628dcdd7c8a · outbound

This paper cites I2hrl: interactive influence-based hierarchical reinforcement learning.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search I2hrl: interactive influence-based hierarchical reinforcement learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.459712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e24e3d98-4de7-4874-a59e-eadec8227ccb · outbound

This paper cites Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Posecnn: A convolutional neural network for 6d object pose estimation in cluttered scenes

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.445458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 16effb18-afed-4b4e-9781-bd489af21cf7 · outbound

This paper cites Hierarchical reinforcement learning with universal policies for multi- step robotic manipulation.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Hierarchical reinforcement learning with universal policies for multi- step robotic manipulation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.432839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fbce350e-0120-469d-b2a4-222c86540ea8 · outbound

This paper cites Learn- ing synergies between pushing and grasping with self- supervised deep reinforcement learning.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Learn- ing synergies between pushing and grasping with self- supervised deep reinforcement learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.419008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d6e7326b-e17f-434f-a3eb-e23bc8223a5a · outbound

This paper cites Transporter networks: Rearranging the visual world for robotic manipulation.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Transporter networks: Rearranging the visual world for robotic manipulation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.407383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 412206d2-d634-4531-8aec-5f1690bb4f56 · outbound

This paper cites Hierarchical policy learning for mechanical search.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Hierarchical policy learning for mechanical search

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.395069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 81dfb5ca-922a-4935-9f4a-25b94de4da2e · outbound

This paper cites Affordance-Driven Next-Best-View Planning for Robotic Grasping.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Affordance-Driven Next-Best-View Planning for Robotic Grasping

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T05:19:06.115930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95667c71-9228-48ec-bc49-f834c6e412a2 · outbound

This paper cites Certifiably Safe Manipulation of Deformable Linear Objects via Joint Shape and Tension Prediction.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search Certifiably Safe Manipulation of Deformable Linear Objects via Joint Shape and Tension Prediction

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:19:06.170529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b325d332-12ca-4133-99b3-326a1c744441 · outbound

This paper cites The policy is optimized with a learning rate of 3×10−4, a discount factor (γ) of 0.99, and a generalized advantage estimation (GAE) parameter (λ) of 0.95.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search The policy is optimized with a learning rate of 3×10−4, a discount factor (γ) of 0.99, and a generalized advantage estimation (GAE) parameter (λ) of 0.95

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.382069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation de7f5108-b645-4853-89a1-2d9b496377f5 · outbound

This paper cites These masked images are then processed by PoseCNN [32], which utilizes a 13-layer VGG16-style convolutional backbone for feature extraction.

XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search These masked images are then processed by PoseCNN [32], which utilizes a 13-layer VGG16-style convolutional backbone for feature extraction

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:19:06.368798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation 385eebb9-88b9-4091-9c8b-489b25694189 · inbound

Certifiably Safe Manipulation of Deformable Linear Objects via Joint Shape and Tension Prediction cites this paper.

Certifiably Safe Manipulation of Deformable Linear Objects via Joint Shape and Tension Prediction XPG-RL: Reinforcement Learning with Explainable Priority Guidance for Efficiency-Boosted Mechanical Search

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:12:22.786309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.