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Paper Citation Record · LEDGER

Masked World Models for Visual Control

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2206.14244.

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

pith.paper-citation-record.v1
2206.14244 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:20:45.269476Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

10
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 436ece58-af47-48ae-a6f2-13179116902f · inbound

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution cites this paper.

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution Masked World Models for Visual Control

Reference 294

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:12:31.215655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-16T08:12:30.984870Z digest=sha256:bca7439419cc16d51be551f7842dce01640646dacd6f472a92ca9998bf7662a0

Observation b4c0c933-3866-4918-b425-25fdd3652df2 · inbound

AutoRAG-LoRA: Hallucination-Triggered Knowledge Retuning via Lightweight Adapters cites this paper.

AutoRAG-LoRA: Hallucination-Triggered Knowledge Retuning via Lightweight Adapters Masked World Models for Visual Control

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T18:20:45.269476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:20:45.269476Z digest=sha256:bac59573fec91193839e05b71a7a4ec971435e776ac8fd7895555bcfefc1f48f

Observation 1df2cb09-57c1-4b31-8f98-826ea248a008 · inbound

Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning cites this paper.

Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning Masked World Models for Visual Control

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-17T21:05:15.589728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T21:04:41.766964Z digest=sha256:f9f61faad402d0ee48e97d3d75e60bcb0b9c6e7699396ffd375d9dd75b71b4a2

Observation ec5532a0-7a5d-497f-82b8-15878675955b · inbound

Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning cites this paper.

Self-Supervised Multisensory Pretraining for Contact-Rich Robot Reinforcement Learning Masked World Models for Visual Control

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-03T21:40:44.392760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T21:40:44.392760Z digest=sha256:9d8b21fe573b1edf31326b6b4a71e7a6f6b7d1a51bbdade67e44d224e2f91cfa

Observation 77cded3d-3248-41c5-a995-86d09f236b35 · inbound

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills cites this paper.

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills Masked World Models for Visual Control

Reference 221

Resolution
unresolved
no resolver link, observed 2026-08-04T19:45:35.189929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:45:35.189929Z digest=sha256:35f7408a231c8961b61c6d3d1280f36d1c2b9f4632824fb281c11a8373cc39af