Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T11:50:26.030339Z
Paper Citation Record · LEDGER
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
As of 5 August 2026, this Paper Citation Record lists 2 of 2 outbound references and 7 inbound Pith citation observations for arXiv:2604.21017.
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 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T10:27:48.057484Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-04T10:49:45.837769Z
Reference resolution
2 of 2 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bce7a904-be84-43c7-9b1d-94fd64c54714 · outbound
This paper cites Why Language Models Hallucinate.
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics Why Language Models Hallucinate
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-05T02:10:36.422039Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 83e3985e-3d98-47ee-8808-f9a56893a752 · outbound
This paper cites Findings of the Association for Computational Linguistics: ACL 2025 , month = jul, year =.
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics Findings of the Association for Computational Linguistics: ACL 2025 , month = jul, year =
Reference 2
- Resolution
- metadata mismatch
- doi, observed 2026-07-05T02:10:36.424730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Pith citing papers
Observation 79d84a65-49f8-40f5-8442-5c38b30894cb · inbound
World Models for Robotic Manipulation: A Survey cites this paper.
World Models for Robotic Manipulation: A Survey Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Reference 147
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T12:33:25.009094Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 85d7913b-b392-47ff-963e-f7cdf2e0773f · inbound
Adversarial Attacks on Learned Policies for Surgical Robotic Tasks cites this paper.
Adversarial Attacks on Learned Policies for Surgical Robotic Tasks Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T10:17:57.718817Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 8052efbd-e856-4a4e-83cc-d448ba13139f · inbound
BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation cites this paper.
BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T10:49:45.839669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation b9d2d570-a9e8-49ce-a817-b232c750e570 · inbound
BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation cites this paper.
BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T21:37:24.142401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 46a2142e-40bf-4ee8-a2b8-ac59091a6ba6 · inbound
BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation cites this paper.
BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T12:41:49.619964Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 91bc1ea3-54f4-4549-ba46-85c45330fe51 · inbound
BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation cites this paper.
BiliVLA: Scene-Aware Vision-Language-Action Model with Reinforcement Learning for Autonomous Biliary Endoscopic Navigation Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T10:27:48.057484Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7abcb81-6fd5-4899-b874-0bd4e3f67830 · inbound
Data Pyramid for Embodied Manipulation cites this paper.
Data Pyramid for Embodied Manipulation Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Reference 289
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T06:18:55.934653Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.