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Paper Citation Record · LEDGER

Beware of Calibration Data for Pruning Large Language Models

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.17711.

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

pith.paper-citation-record.v1
2410.17711 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:52:43.503944Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T23:50:31.870783Z

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 7eaaa16e-2c94-44f2-8059-7dbb7782ec26 · inbound

Pruning Weights but Not Truth: Safeguarding Truthfulness While Pruning LLMs cites this paper.

Pruning Weights but Not Truth: Safeguarding Truthfulness While Pruning LLMs Beware of Calibration Data for Pruning Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T16:52:43.503944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:52:43.503944Z digest=sha256:718ee7db5fbf84b660c4faeba02fb7688d4bd107cee8ec067d3167622fd6d3be

Observation e0f8cf12-d4a8-4a7b-ade6-60012bbaa492 · inbound

LUQ: Layerwise Ultra-Low Bit Quantization for Multimodal Large Language Models cites this paper.

LUQ: Layerwise Ultra-Low Bit Quantization for Multimodal Large Language Models Beware of Calibration Data for Pruning Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-04T14:45:26.011445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T14:45:26.011445Z digest=sha256:3d305959d0d8785d78849c90ccebd199ae4b73ee8fc4f5eb8f1036ad2d13bf92

Observation 5047fceb-ed5a-466d-91d1-857a6fcffbc1 · inbound

A Metamorphic Testing Perspective on Knowledge Distillation for Language Models of Code: Does the Student Deeply Mimic the Teacher? cites this paper.

A Metamorphic Testing Perspective on Knowledge Distillation for Language Models of Code: Does the Student Deeply Mimic the Teacher? Beware of Calibration Data for Pruning Large Language Models

Reference 65

Resolution
verified exact
arxiv_id, observed 2026-05-17T23:50:31.873482Z

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.

source=pdf_text observed=2026-05-17T23:45:54.490984Z digest=sha256:3be6d29010f6e503bef4594fce03c03f42d4179c44ecae6c055c983c3c1719cd