Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.05015.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T05:19:39.366974Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T11:36:55.536283Z
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 118ceff0-c3ca-432c-be65-e4512a181769 · inbound
Olica: Efficient Structured Pruning of Large Language Models without Retraining cites this paper.
Olica: Efficient Structured Pruning of Large Language Models without Retraining Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:19:39.366974Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 13c54924-4a5c-49da-ab09-b2bef57572b6 · inbound
SDMPrune: Self-Distillation MLP Pruning for Efficient Large Language Models cites this paper.
SDMPrune: Self-Distillation MLP Pruning for Efficient Large Language Models Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:18:00.717102Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 487fcc5f-1e92-4ee8-b0c6-fcdd4c193f07 · inbound
Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models cites this paper.
Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T11:47:18.960006Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19c934f2-7efc-4d1c-86eb-25a2facb359e · inbound
Less is MoE: Trimming Experts in Domain-Specialist Language Models cites this paper.
Less is MoE: Trimming Experts in Domain-Specialist Language Models Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T11:36:55.537834Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 2d2f3485-a7b0-4bc9-bdb3-d0a059dbdee0 · inbound
SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling cites this paper.
SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling Compresso: Structured Pruning with Collaborative Prompting Learns Compact Large Language Models
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T09:51:03.338653Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.