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Paper Citation Record · LEDGER

DeepMDP: Learning Continuous Latent Space Models for Representation Learning

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1906.02736.

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

pith.paper-citation-record.v1
1906.02736 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 2026-08-05T06:32:48.257954+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T07:20:40.388492Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-19T09:17:14.033750Z

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 8a342998-c48d-4020-8745-41c436fdd7c6 · inbound

Dream to Control: Learning Behaviors by Latent Imagination cites this paper.

Dream to Control: Learning Behaviors by Latent Imagination DeepMDP: Learning Continuous Latent Space Models for Representation Learning

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-12T01:16:36.487120Z

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.

source=pdf_text observed=2026-05-12T01:16:36.399272Z digest=sha256:e6d2937895e38ccf5d81e6bc4b95500f1bb56639d4b385dd2d2ea639714737a2

Observation 7a4a5647-27e8-437c-8696-c95a27a7fb40 · inbound

R3M: A Universal Visual Representation for Robot Manipulation cites this paper.

R3M: A Universal Visual Representation for Robot Manipulation DeepMDP: Learning Continuous Latent Space Models for Representation Learning

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-05-15T13:26:54.035793Z

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.

source=pdf_text observed=2026-05-15T13:26:53.843613Z digest=sha256:ddc22b0a5a00ce653c54d1eff8c12324d5c776623ae94e9f40f04118d8c6e9b0

Observation 2fa42e76-feb4-4ae7-a524-497cb39c8e9f · inbound

Self-Predictive Representations for Combinatorial Generalization in Behavioral Cloning cites this paper.

Self-Predictive Representations for Combinatorial Generalization in Behavioral Cloning DeepMDP: Learning Continuous Latent Space Models for Representation Learning

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-05-19T09:17:14.036535Z

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.

source=pdf_text observed=2026-05-19T09:15:45.511104Z digest=sha256:2ada5ae1693ee08352ec4c03800bcd043618a9de3570500bcba217f6904cac59

Observation c56ea0ff-e4ec-4ba8-b145-965320a9ce7b · inbound

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning cites this paper.

Multi-scale Predictive Representations for Goal-conditioned Reinforcement Learning DeepMDP: Learning Continuous Latent Space Models for Representation Learning

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:16:26.276342Z

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.

source=pdf_text observed=2026-05-12T03:35:37.739085Z digest=sha256:fa18a72403346f4880d39ca5f2a27d393821c3f2089a786aecd97aa66ec83397

Observation 6d4d84bb-1c77-4969-b53d-bb5e3a81d7e7 · inbound

When Does Reward Teach State? A Hidden-Automaton Instrument and the Group-Language Boundary cites this paper.

When Does Reward Teach State? A Hidden-Automaton Instrument and the Group-Language Boundary DeepMDP: Learning Continuous Latent Space Models for Representation Learning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-02T07:20:40.388492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T07:20:40.388492Z digest=sha256:6106fffdee76c6dcb2210678ffbe9aa03a19ea26d7b28005eb4e76f477df157f