Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2007.11091.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T01:06:18.561088Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T07:51:16.548910Z
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 079e9831-c32d-4426-8fd2-17a6e83aecf6 · inbound
What Matters in Learning from Offline Human Demonstrations for Robot Manipulation cites this paper.
What Matters in Learning from Offline Human Demonstrations for Robot Manipulation EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T08:51:55.950585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9a706c9c-1b13-42de-8294-31444d9fff6a · inbound
Visual Pre-Training on Unlabeled Images using Reinforcement Learning cites this paper.
Visual Pre-Training on Unlabeled Images using Reinforcement Learning EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T01:06:18.561088Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42acfa00-10cb-44a1-9353-437dd73ac8d8 · inbound
Abstraction for Offline Goal-Conditioned Reinforcement Learning cites this paper.
Abstraction for Offline Goal-Conditioned Reinforcement Learning EMaQ: Expected-Max Q-Learning Operator for Simple Yet Effective Offline and Online RL
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T07:51:16.552201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.