Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T15:52:38.462697Z
Paper Citation Record · LEDGER
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives
As of 22 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2509.21256.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
21 of 21 outbound references displayed
- verified exact3
- verified fuzzy7
- unresolved11
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ea1eb302-73eb-41d3-8a99-88d45b7e0f6d · outbound
This paper cites an unresolved cited work.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T15:52:38.824492Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 18d295c7-c1ac-4626-a57b-a5684c0e1c80 · outbound
This paper cites D-CODA: Diffusion for Coordinated Dual-Arm Data Augmentation.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives D-CODA: Diffusion for Coordinated Dual-Arm Data Augmentation
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T15:52:38.753109Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 456959d4-8736-4618-9dfb-3b2ebb6116e2 · outbound
This paper cites Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:52:38.381035Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eba7aca7-3f7f-48da-b255-f1969568a990 · outbound
This paper cites Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:52:38.386747Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 20419d07-d540-4f2b-9fb6-285c49d90aa6 · outbound
This paper cites Planning of graspless ma- nipulation by multiple robot fingers.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Planning of graspless ma- nipulation by multiple robot fingers
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T15:52:38.896212Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 215c9a9f-e8a1-4144-a391-1b68f32c84ee · outbound
This paper cites Georgios Papagiannis, Norman Di Palo, Pietro Vitiello, and Edward Johns.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Georgios Papagiannis, Norman Di Palo, Pietro Vitiello, and Edward Johns
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:52:38.397654Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ffe2b9d3-7702-46fb-8be0-490a6ca67dd3 · outbound
This paper cites Learning Pivoting Manipulation with Force and Vision Feedback Using Optimization-based Demonstrations.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Learning Pivoting Manipulation with Force and Vision Feedback Using Optimization-based Demonstrations
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:52:38.409398Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f8c694b-b07e-477d-b27c-eab1a3f1b93b · outbound
This paper cites Dexterous Non-Prehensile Manipulation for Ungraspable Object via Extrinsic Dexterity.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Dexterous Non-Prehensile Manipulation for Ungraspable Object via Extrinsic Dexterity
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:52:38.415237Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53f55b61-4080-4fc6-ada8-6653f018ca07 · outbound
This paper cites In the Wild Ungraspable Object Picking with Bimanual Nonprehensile Manipulation.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives In the Wild Ungraspable Object Picking with Bimanual Nonprehensile Manipulation
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T15:52:38.627818Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 78f054c7-8b6d-44db-96a1-10f7fa2800ec · outbound
This paper cites Dexsingrasp: Learning a unified policy for dexterous object singulation and grasping in cluttered environments.arXiv preprint arXiv:2504.04516, 2025a.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Dexsingrasp: Learning a unified policy for dexterous object singulation and grasping in cluttered environments.arXiv preprint arXiv:2504.04516, 2025a
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:52:38.426018Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f949048d-0f2a-4e33-b327-0c041d54557b · outbound
This paper cites ActivePusher: Active Learning and Planning with Residual Physics for Nonprehensile Manipulation.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives ActivePusher: Active Learning and Planning with Residual Physics for Nonprehensile Manipulation
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:52:38.430744Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation baf501ac-de92-4c71-a729-38f0678bd23d · outbound
This paper cites From the resulting 50 frames per trial, we manually annotate the start and end frames of each task.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives From the resulting 50 frames per trial, we manually annotate the start and end frames of each task
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T15:52:38.842235Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation dfe95a12-22b7-49ef-bc35-0cabb475d283 · outbound
This paper cites Instead, we select the farthest point from the active end-effector on the object’s point cloud as the anchor point, which allows a stable update of Eqn.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Instead, we select the farthest point from the active end-effector on the object’s point cloud as the anchor point, which allows a stable update of Eqn
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T15:52:38.807755Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 85594e2e-a9d2-4411-8335-d832aa3e9acf · outbound
This paper cites blue basket.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives blue basket
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T15:52:38.790339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 82832d63-51fa-45ea-bf3d-580f5418ab34 · outbound
This paper cites an unresolved cited work.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Unresolved cited work
Reference 2012
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T15:52:38.859186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation ea25cf9f-be18-4944-8535-eb40bb7e2df5 · outbound
This paper cites Proximal Policy Optimization Algorithms.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Proximal Policy Optimization Algorithms
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:52:38.403507Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation af41d9ec-fa35-4268-8a55-cf9bbab06887 · outbound
This paper cites ParticleFormer: A 3D Point Cloud World Model for Multi-Object, Multi-Material Robotic Manipulation.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives ParticleFormer: A 3D Point Cloud World Model for Multi-Object, Multi-Material Robotic Manipulation
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:52:38.364685Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 37158d45-028a-4093-92fc-7de2ac42b8c8 · outbound
This paper cites Robust execution of contact-rich motion plans by hybrid force- velocity control.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Robust execution of contact-rich motion plans by hybrid force- velocity control
Reference 2020
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T15:52:38.913180Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation a16fdfc5-a92f-4655-8741-06a5eb94ee47 · outbound
This paper cites Do you need a hand?–a bimanual robotic dressing assistance scheme.IEEE Transactions on Robotics, 40:1906–1919,.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Do you need a hand?–a bimanual robotic dressing assistance scheme.IEEE Transactions on Robotics, 40:1906–1919,
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T15:52:38.878840Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 6acd3d2a-4eca-4db8-97f1-3cd43dcf0195 · outbound
This paper cites Peract2: Benchmark- ing and learning for robotic bimanual manipulation tasks.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Peract2: Benchmark- ing and learning for robotic bimanual manipulation tasks
Reference 2024
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T15:52:38.931246Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Observation 0ca1eac2-0c83-4109-bdf3-30ad6cee9909 · outbound
This paper cites Hacman++: Spatially- grounded motion primitives for manipulation.
BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives Hacman++: Spatially- grounded motion primitives for manipulation
Reference 2025
- Resolution
- verified exact
- doi, observed 2026-08-15T15:52:38.518977Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.
Pith citing papers
No inbound Pith citation observations are available.