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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 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 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:44:29.744748Z

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 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.

source=pdf_text observed=2026-08-07T15:44:29.744748Z digest=sha256:5fde45054fe0611bdbb6f0c6ef9936abda46f7a5536e30e82c70eabc3f110c4f

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.

source=arxiv_source observed=2026-08-06T22:30:28.809315Z digest=sha256:b1c56a3df73bb21fa1b56dae33f89eed08fb3530d0b832bb5e413f97b014f28f

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.

source=pdf_text observed=2026-08-05T15:43:58.776776Z digest=sha256:da167de5e9da2f65b6aa371f285a86bc99294fedb4c937f9f243cf6ba812299c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-14T20:31:50.043920Z digest=sha256:9d41c7ed1d081ad0a3eb76d7739f38a3308da623ede8825a97ab33a0fe6c7b58

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T17:24:32.311565Z digest=sha256:205ce877cab79c3723fb3b2efe167e3cacfe82b2ed3f14bed07e9d5b9f2872b3