Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
ETHIC: Evaluating Large Language Models on Long-Context Tasks with High Information Coverage
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.16848.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T16:11:18.544009Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T22:02:42.098639Z
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 43a8759a-9757-47ea-8e2a-8842b90ae72b · inbound
DebateBench: A Challenging Long Context Reasoning Benchmark For Large Language Models cites this paper.
DebateBench: A Challenging Long Context Reasoning Benchmark For Large Language Models ETHIC: Evaluating Large Language Models on Long-Context Tasks with High Information Coverage
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:11:18.544009Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6ac36575-d17c-4731-8683-e28c29e9355e · inbound
DICE-BENCH: Evaluating the Tool-Use Capabilities of Large Language Models in Multi-Round, Multi-Party Dialogues cites this paper.
DICE-BENCH: Evaluating the Tool-Use Capabilities of Large Language Models in Multi-Round, Multi-Party Dialogues ETHIC: Evaluating Large Language Models on Long-Context Tasks with High Information Coverage
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T22:02:42.211387Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.