Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.11802.
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 2026-08-07T14:20:25.752009Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T05:00:21.837128Z
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 16b931d1-cca0-4832-86c7-03529d525cb7 · inbound
100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability? cites this paper.
100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability? Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language Models
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:20:25.752009Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ccd3baa-49a3-4c3f-aabd-9f5bb6097bfc · inbound
MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models cites this paper.
MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language Models
Reference 72
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:08:12.726053Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12fa92ed-3aa3-45b5-b1e3-ed4622414560 · inbound
Ref-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models cites this paper.
Ref-Long: Benchmarking the Long-context Referencing Capability of Long-context Language Models Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language Models
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:59:55.426052Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8075076c-ab8c-42af-9475-5807a2d90d83 · inbound
NeMo: Needle in a Montage for Video-Language Understanding cites this paper.
NeMo: Needle in a Montage for Video-Language Understanding Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language Models
Reference 66
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:54:21.003595Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 89425d64-ea27-4ecb-a284-01e938271b2d · inbound
Positional Failures in Long-Context LLMs: A Blind Spot in Reasoning Benchmarks cites this paper.
Positional Failures in Long-Context LLMs: A Blind Spot in Reasoning Benchmarks Counting-Stars: A Multi-evidence, Position-aware, and Scalable Benchmark for Evaluating Long-Context Large Language Models
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T05:00:21.839923Z
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.