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Paper Citation Record · LEDGER

Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.15618.

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

pith.paper-citation-record.v1
2502.15618 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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T11:54:03.411984Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:21:35.649075Z

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 bb593e52-c73e-4260-b528-31a4ceb3afed · inbound

RAP: Runtime Adaptive Pruning for LLM Inference cites this paper.

RAP: Runtime Adaptive Pruning for LLM Inference Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:21:35.651616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-22T13:20:41.739571Z digest=sha256:7dc65b7e14d9459061087e07017cb251f8ab3cfb90a542a33eaf14c62b6fd7d4

Observation 7f341017-b36d-4d01-8a17-7924c9ad5817 · inbound

TriSP: Tri-Signal Structured Pruning for Large Language Models cites this paper.

TriSP: Tri-Signal Structured Pruning for Large Language Models Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-02T11:54:03.411984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:54:03.411984Z digest=sha256:8ca151432b65b7a608dacb64c7578755d23831f0c10959dd7eececb142348654