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Paper Citation Record · LEDGER

Reinforcement Learning with Videos: Combining Offline Observations with Interaction

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2011.06507.

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

pith.paper-citation-record.v1
2011.06507 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:18:45.077358Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T02:26:26.983106Z

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 02ca4761-2275-49fa-9386-b9ce34d322e5 · inbound

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training cites this paper.

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T04:42:52.797242Z

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=2026-05-15T04:42:52.627166Z digest=sha256:63f1d0d4ac88f7e181f9cea7269f7f43895794a39c243f6790f640a9fb9b354f

Observation 152559fe-8c23-40d5-9e7e-eadec3b70019 · inbound

Learning Interactive Real-World Simulators cites this paper.

Learning Interactive Real-World Simulators Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reference 208

Resolution
verified exact
arxiv_id, observed 2026-05-16T02:15:18.399607Z

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=2026-05-16T02:15:18.265190Z digest=sha256:980d62e8533950edec77b9545a42943abf0f56ace6819e143e84579a911702b1

Observation a0bb9b71-31c6-45bd-a161-aeeabd9824fa · inbound

Latent Action Learning Requires Supervision in the Presence of Distractors cites this paper.

Latent Action Learning Requires Supervision in the Presence of Distractors Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-09T19:18:45.077358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T19:18:45.077358Z digest=sha256:65aae0136324f6bc4dc30550b5f52da644f1f318533241b5db566e2f8ab52b00

Observation df42e165-53d6-48f8-81fd-cad8a9b57618 · inbound

AMPLIFY: Actionless Motion Priors for Robot Learning from Videos cites this paper.

AMPLIFY: Actionless Motion Priors for Robot Learning from Videos Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-07T00:25:28.401214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:25:28.401214Z digest=sha256:b1704eadef3571eef818c7d331ad16e46f6564d8ea9b7b52444665411653ba9f

Observation ab37548c-2fff-4d3b-969f-54d633107bee · inbound

Veo-Act: How Far Can Frontier Video Models Advance Generalizable Robot Manipulation? cites this paper.

Veo-Act: How Far Can Frontier Video Models Advance Generalizable Robot Manipulation? Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-10T22:10:49.477131Z

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=2026-05-10T20:10:54.362107Z digest=sha256:f0461dc984ac48c369c219aa98ef7dc879423271ea562f1d854e5a4e0aea7f36

Observation d1b78812-4e95-444d-981f-0644fc40ee8d · inbound

Dual Hierarchical Dialogue Policy Learning for Legal Inquisitive Conversational Agents cites this paper.

Dual Hierarchical Dialogue Policy Learning for Legal Inquisitive Conversational Agents Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reference 128

Resolution
verified exact
arxiv_id, observed 2026-05-15T05:25:04.806926Z

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=2026-05-15T05:21:09.512348Z digest=sha256:f2686b3719610e997beb6e8ff115faa9a9ca54594f2e8ef867add7fd5156aa86

Observation 502eaaff-2860-4784-8630-a64041d524bc · inbound

Dual Hierarchical Dialogue Policy Learning for Legal Inquisitive Conversational Agents cites this paper.

Dual Hierarchical Dialogue Policy Learning for Legal Inquisitive Conversational Agents Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reference 128

Resolution
verified exact
arxiv_id, observed 2026-05-19T13:52:20.058353Z

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=2026-05-19T13:49:16.876877Z digest=sha256:37a55ca86261356347a64c25ddb09705799839bb7ca03a1b93a000c826f10c86

Observation 39e25f3a-491a-43ab-9f77-87a76d861e4f · inbound

Reinforcement Learning from Cross-domain Videos with Video Prediction Model cites this paper.

Reinforcement Learning from Cross-domain Videos with Video Prediction Model Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-02T02:26:26.984783Z

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=2026-06-28T10:54:49.582908Z digest=sha256:1bcc8dab70bc8eca5d96c756ead4a9d40b99b4faf91653ea669946047b9006d8

Observation d45850c3-d5f8-4230-a827-d9f5a65d8266 · inbound

Reinforcement Learning: From Algorithms To Foundation Models cites this paper.

Reinforcement Learning: From Algorithms To Foundation Models Reinforcement Learning with Videos: Combining Offline Observations with Interaction

Reference 223

Resolution
unresolved
no resolver link, observed 2026-08-01T17:45:18.166411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T17:45:18.166411Z digest=sha256:d69c9b2a963878503d4870c56dd272d86c651d33766c63ab5eb870016b6b9799