Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.14947.
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 2026-08-07T15:02:38.559536Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T00:42:04.061794Z
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 0eeeaadc-08dc-4a66-9c9d-d3821bb1025b · inbound
Advancing the Scientific Method with Large Language Models: From Hypothesis to Discovery cites this paper.
Advancing the Scientific Method with Large Language Models: From Hypothesis to Discovery How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:02:38.559536Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fa346af3-6301-42b3-bcc5-58d20e21c54d · inbound
Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law cites this paper.
Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T00:42:04.171085Z
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.