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Paper Citation Record · LEDGER

Deep Dynamics Models for Learning Dexterous Manipulation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1909.11652.

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

pith.paper-citation-record.v1
1909.11652 v1

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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:03:47.644501Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T19:38:56.329177Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1e10007d-17b7-4ff7-9881-9f4a65ca309f · inbound

DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning cites this paper.

DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning Deep Dynamics Models for Learning Dexterous Manipulation

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-17T16:06:09.551942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-17T16:06:09.448517Z digest=sha256:91521074c45bd4e139aee0dd4f84ab69370852d0f62c80cd971f133ed6b23ef8

Observation 8de4fcca-fc38-43a3-a230-aa0ca047e3ea · inbound

Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens cites this paper.

Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens Deep Dynamics Models for Learning Dexterous Manipulation

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T06:03:47.644501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:03:47.644501Z digest=sha256:0d5a5928813a526e5046984842ccf87a53cb35a1f6f03d69823d5d417452d237

Observation 620b047f-42dc-4131-90cf-f175a2d05b72 · inbound

ClutterDexGrasp: A Sim-to-Real System for General Dexterous Grasping in Cluttered Scenes cites this paper.

ClutterDexGrasp: A Sim-to-Real System for General Dexterous Grasping in Cluttered Scenes Deep Dynamics Models for Learning Dexterous Manipulation

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T00:23:18.344879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:23:18.344879Z digest=sha256:ba76607ea85a5fc857403841a2d3c5ece3ece3f6268f5084735a9515b87c73f2

Observation 6c80de7a-4553-45bc-a41c-d1449a14bc5b · inbound

GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Training cites this paper.

GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Training Deep Dynamics Models for Learning Dexterous Manipulation

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T16:38:26.401531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T16:38:26.401531Z digest=sha256:33d2eca4ace985dc54e4b74ffc6a309c542d13f45dd8427f3fe8e4adc664742d

Observation a9217a7a-6a4e-49e1-acca-7626da8dc0bf · inbound

DiLA: Disentangled Latent Action World Models cites this paper.

DiLA: Disentangled Latent Action World Models Deep Dynamics Models for Learning Dexterous Manipulation

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-20T19:38:56.331449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T19:35:37.527479Z digest=sha256:6aea3682bc54f4fe608aefe8a74b5ad8ca618d85480b7a7a09c4078a4421dd44