Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.12200.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T14:57:27.645472Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T09:02:14.518612Z
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 39140dc0-ce8b-45ab-80bf-e1d8715e6492 · inbound
FTP: A Fine-grained Token-wise Pruner for Large Language Models via Token Routing cites this paper.
FTP: A Fine-grained Token-wise Pruner for Large Language Models via Token Routing APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:57:27.645472Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cbffbc6e-f309-4b74-9466-41507d492341 · inbound
FineGates: LLMs Finetuning with Compression using Stochastic Gates cites this paper.
FineGates: LLMs Finetuning with Compression using Stochastic Gates APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T13:37:39.109971Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aee10fc1-99f2-4a51-8972-51ec7728b6b9 · inbound
MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs cites this paper.
MaskPro: Linear-Space Probabilistic Learning for Strict (N:M)-Sparsity on LLMs APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T09:02:14.522226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.