Paper Citation Record · LEDGER

What Will it Take to Fix Benchmarking in Natural Language Understanding?

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2104.02145.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2104.02145 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:54:32.977436Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-01T21:16:13.549729Z

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 114205d4-b6f3-48d4-b9a4-18830077255b · inbound

GPAI Evaluations Standards Taskforce: Towards Effective AI Governance cites this paper.

GPAI Evaluations Standards Taskforce: Towards Effective AI Governance What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T15:54:32.977436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c93d6f05-293f-4694-83ec-c08040ca669e · inbound

Towards Effective Discrimination Testing for Generative AI cites this paper.

Towards Effective Discrimination Testing for Generative AI What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T23:08:44.109938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f633ecc-145a-4fa1-99df-696893cb17e7 · inbound

Do Large Language Model Benchmarks Test Reliability? cites this paper.

Do Large Language Model Benchmarks Test Reliability? What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-09T04:45:34.570985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5161b5c4-8a12-4a33-a9a2-18c05efa0da6 · inbound

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation cites this paper.

AUTOLAW: Enhancing Legal Compliance in Large Language Models via Case Law Generation and Jury-Inspired Deliberation What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T15:44:29.744748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2aadb985-3932-4443-9b5c-20ebf50d25b2 · inbound

Potemkin Understanding in Large Language Models cites this paper.

Potemkin Understanding in Large Language Models What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T22:30:28.809315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7b0d58c-24b5-4c16-808e-07ea8fb92706 · inbound

Private, Verifiable, and Auditable AI Systems cites this paper.

Private, Verifiable, and Auditable AI Systems What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-05T15:43:58.776776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8741e97a-d21d-4b4d-8341-40c8bcb021d2 · inbound

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack cites this paper.

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:32:56.901133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4dd1879b-a8f5-47f6-8591-e7ad02767f45 · inbound

The Case for Model Science: Verify, Explore, Steer, Refine cites this paper.

The Case for Model Science: Verify, Explore, Steer, Refine What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:16:13.551591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 278c8f23-f6ca-4367-9807-70f3fc487741 · inbound

Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA cites this paper.

Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA What Will it Take to Fix Benchmarking in Natural Language Understanding?

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-08-11T10:20:58.755608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.