Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.19668.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T22:50:34.140276Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T22:21:49.407343Z
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 4eff357b-0b1b-4dae-9a4b-5508821a0fdc · inbound
Value-Based Deep RL Scales Predictably cites this paper.
Value-Based Deep RL Scales Predictably DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T22:50:34.140276Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f10747d-6b07-4af0-b75b-552092ec3032 · inbound
The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning cites this paper.
The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:32:53.901414Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3b6e9519-2ae4-4ab0-9ec0-1e12b356ec73 · inbound
Residual Reward Models for Preference-based Reinforcement Learning cites this paper.
Residual Reward Models for Preference-based Reinforcement Learning DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:17:42.181860Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3de77387-dce0-45db-97f7-38563c7bb890 · inbound
A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control cites this paper.
A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:31:07.879014Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f8b3b226-75c5-494c-afe0-743973e53027 · inbound
Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations cites this paper.
Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T22:21:49.484256Z
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.
Observation f6fc8ad4-a7f3-4c12-bc63-ee0b631429fb · inbound
Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations cites this paper.
Agent-Centric Observation Adaptation for Robust Visual Control under Dynamic Perturbations DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T00:50:49.824477Z
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.
Observation dade4dfc-3cb6-401e-85af-588d4fab6a1f · inbound
Reinforcement Learning for the Full Strawberry Harvesting Process: Obstacle Separation, Detachment, and Placement cites this paper.
Reinforcement Learning for the Full Strawberry Harvesting Process: Obstacle Separation, Detachment, and Placement DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T01:23:37.685746Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.