Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On the State of the Art of Evaluation in Neural Language Models
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1707.05589.
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 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-29T18:45:27.282354Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-06-29T18:53:51.687415Z
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 1b1e8989-d15c-41a1-8bd2-7af127ac3330 · inbound
Reproducibility in Machine Learning for Health cites this paper.
Reproducibility in Machine Learning for Health On the State of the Art of Evaluation in Neural Language Models
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T11:05:40.151330Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bf7b805a-1c64-4fbf-bb1a-9cf86a856411 · inbound
Compressive Transformers for Long-Range Sequence Modelling cites this paper.
Compressive Transformers for Long-Range Sequence Modelling On the State of the Art of Evaluation in Neural Language Models
Reference 98
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-18T10:46:16.693638Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e004080e-485e-497c-9380-eb1a8281fd2b · inbound
ChemCrow: Augmenting large-language models with chemistry tools cites this paper.
ChemCrow: Augmenting large-language models with chemistry tools On the State of the Art of Evaluation in Neural Language Models
Reference 107
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T19:05:23.061616Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c95e32bb-6a2d-476d-986b-f30c1c165f64 · inbound
Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior cites this paper.
Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior On the State of the Art of Evaluation in Neural Language Models
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-05-23T02:42:26.403393Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 63d82e32-de37-4beb-be5d-d7c1915137bf · inbound
Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior cites this paper.
Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior On the State of the Art of Evaluation in Neural Language Models
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-05-25T07:55:33.109434Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1b8318a1-4a4d-42b2-8970-983d268da28e · inbound
Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models cites this paper.
Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models On the State of the Art of Evaluation in Neural Language Models
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T23:44:26.546870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3c99588c-8aa1-48f0-a58d-32d658983659 · inbound
When do complex-valued neural networks help? A study of representation, geometry, and optimization cites this paper.
When do complex-valued neural networks help? A study of representation, geometry, and optimization On the State of the Art of Evaluation in Neural Language Models
Reference 28
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T18:53:51.689041Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.