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Paper Citation Record · LEDGER

Careful Selection of Knowledge to solve Open Book Question Answering

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1907.10738.

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

pith.paper-citation-record.v1
1907.10738 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:46:42.907393Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T02:37:07.869989Z

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 e6bd628b-c225-450c-a3f3-7c4bd75b14b7 · inbound

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks cites this paper.

TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks Careful Selection of Knowledge to solve Open Book Question Answering

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:42.907393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:46:42.907393Z digest=sha256:cdbea0fab54c7c5308802215654b72f9853fe08191e79c55e56cc9e183638c0e

Observation 22d13947-df0a-4219-b21b-21f1d7155a44 · inbound

ADMM-Q: An Improved Hessian-based Weight Quantizer for Post-Training Quantization of Large Language Models cites this paper.

ADMM-Q: An Improved Hessian-based Weight Quantizer for Post-Training Quantization of Large Language Models Careful Selection of Knowledge to solve Open Book Question Answering

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-04T23:49:36.405808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T02:35:25.946090Z digest=sha256:8c178a1cccf8ad9325007c39b449155fd180aef27a54014e898814bf688922af