Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Fast and Effective Weight Update for Pruned Large Language Models
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2401.02938.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T19:42:41.336372Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T22:06:16.850564Z
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 e1b76240-4ede-4dc1-a59b-83659f64b14d · inbound
ProxSparse: Regularized Learning of Semi-Structured Sparsity Masks for Pretrained LLMs cites this paper.
ProxSparse: Regularized Learning of Semi-Structured Sparsity Masks for Pretrained LLMs Fast and Effective Weight Update for Pruned Large Language Models
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T19:42:41.336372Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9195d14a-72be-4621-9a73-eafa125b9765 · 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 Fast and Effective Weight Update for Pruned Large Language Models
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:37:07.853703Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 46e6833c-f47f-424d-b463-9f44c45397aa · inbound
LEAP: Learnable End-to-End Adaptive Pruning of Large Language Models cites this paper.
LEAP: Learnable End-to-End Adaptive Pruning of Large Language Models Fast and Effective Weight Update for Pruned Large Language Models
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T13:38:19.282971Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 3dda1cf2-9422-4e21-b4bf-34aa5de29ae9 · inbound
LEAP: Learnable End-to-End Adaptive Pruning of Large Language Models cites this paper.
LEAP: Learnable End-to-End Adaptive Pruning of Large Language Models Fast and Effective Weight Update for Pruned Large Language Models
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T19:15:01.102436Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 87035746-afc2-4a2c-9c93-2259b2a927db · inbound
CRePE: Convolution-aware Relative Importance in Post-training Pruning with Efficient Search cites this paper.
CRePE: Convolution-aware Relative Importance in Post-training Pruning with Efficient Search Fast and Effective Weight Update for Pruned Large Language Models
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-01T22:06:16.852636Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.