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Paper Citation Record · LEDGER

SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1808.05326.

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

pith.paper-citation-record.v1
1808.05326 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:10:32.778509Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T20:53:17.419718Z

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 e0e3d736-4b4d-45d3-b39a-6300f927aea1 · inbound

OPT: Open Pre-trained Transformer Language Models cites this paper.

OPT: Open Pre-trained Transformer Language Models SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

Reference 90

Resolution
verified exact
arxiv_id, observed 2026-07-04T22:59:28.152591Z

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=2026-05-10T20:53:16.720145Z digest=sha256:badb8b550f70b5752983a794af679b73dbb90cdd3eb8e67e0f7564f50a9891ce

Observation 5478c680-df05-4bb1-bc29-4d62599a3706 · inbound

Advancing Reasoning in Large Language Models: Promising Methods and Approaches cites this paper.

Advancing Reasoning in Large Language Models: Promising Methods and Approaches SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-09T04:10:32.778509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T04:10:32.778509Z digest=sha256:60c5248ead9fb45d62348fec4913d5945ccfb6f05d6349251b09f682d0983b9a

Observation 5758bc55-11c6-49eb-b9a4-53610d748c45 · inbound

Toward Better Generalisation in Uncertainty Estimators: Leveraging Data-Agnostic Features cites this paper.

Toward Better Generalisation in Uncertainty Estimators: Leveraging Data-Agnostic Features SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T20:02:05.089866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:02:05.089866Z digest=sha256:b1be5369049219aedeb0c30d6b72302f73e9eca39a90aa4bda4b67deb536a7dd

Observation 85a1d04b-36e5-40f6-809e-a3ac0438fc44 · inbound

LENS: Learning Ensemble Confidence from Neural States for Multi-LLM Answer Integration cites this paper.

LENS: Learning Ensemble Confidence from Neural States for Multi-LLM Answer Integration SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T11:03:16.630904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:03:16.630904Z digest=sha256:b40bc834d00383fc264b3b0f38ac0b31d6c99880ce8e5f204057831988c6a83b