Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.11793.
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 2026-08-07T13:53:52.775613Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T10:37:56.806960Z
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 b5db2ba4-1378-4f72-96c2-e695dd024b0d · inbound
GIFARC: Synthetic Dataset for Leveraging Human-Intuitive Analogies to Elevate AI Reasoning cites this paper.
GIFARC: Synthetic Dataset for Leveraging Human-Intuitive Analogies to Elevate AI Reasoning Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:53:52.775613Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46d4d49d-7e76-4b38-9667-54e40d961391 · inbound
Slots, Transitions, Loops: Learning Composable World Models for ARC cites this paper.
Slots, Transitions, Loops: Learning Composable World Models for ARC Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T10:37:56.808539Z
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.