Paper Citation Record · LEDGER

ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2310.02998.

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

pith.paper-citation-record.v1
2310.02998 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:35:34.700857Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T15:25:48.347109Z

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 344b9015-776b-4c94-affa-9a911504e288 · inbound

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models cites this paper.

EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T12:09:08.047002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 108f4519-7f3b-407b-8cb0-8b9a86c5a6be · inbound

LinMU: Multimodal Understanding Made Linear cites this paper.

LinMU: Multimodal Understanding Made Linear ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-16T18:33:15.177085Z

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.

Observation 40d587a7-89bd-4d37-83eb-e029829d6cce · inbound

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs cites this paper.

When AI Reviews Its Own Code: Recursive Self-Training Collapse in Code LLMs ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:25:48.348921Z

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.

Observation 4c359f4e-44b5-40b4-aaa8-651877fe24e6 · inbound

AWARe: Mitigating Catastrophic Forgetting via Activation-Weighted Adaptive REtention cites this paper.

AWARe: Mitigating Catastrophic Forgetting via Activation-Weighted Adaptive REtention ECoFLaP: Efficient Coarse-to-Fine Layer-Wise Pruning for Vision-Language Models

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-16T00:35:34.700857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.