Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraft
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2312.09238.
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 2026-08-04T19:45:34.890137Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation b208de04-6d1c-4df6-a251-44cad5928692 · inbound
MIMIC-Py: An Extensible Tool for Personality-Driven Automated Game Testing with Large Language Models cites this paper.
MIMIC-Py: An Extensible Tool for Personality-Driven Automated Game Testing with Large Language Models Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraft
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T00:45:50.532633Z
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 fa7d6cf9-2de4-469a-9cbe-3017f2cee930 · inbound
QVal: Cheaply Evaluating Dense Supervision Signals for Long-Horizon LLM Agents cites this paper.
QVal: Cheaply Evaluating Dense Supervision Signals for Long-Horizon LLM Agents Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraft
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T06:05:29.000069Z
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 7c4141df-eda4-4595-8597-a711f02b5395 · inbound
Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills cites this paper.
Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills Auto MC-Reward: Automated Dense Reward Design with Large Language Models for Minecraft
Reference 136
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T19:45:34.890137Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.