Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Sparsity Meets Similarity: Leveraging Long-Tail Distribution for Dynamic Optimized Token Representation in Multimodal Large Language Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.01162.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:22:37.891208Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T12:46:04.832652Z
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 00fd528a-580c-476a-9dff-37e14e2d1699 · inbound
Grounding-Aware Token Pruning: Recovering from Drastic Performance Drops in Visual Grounding Caused by Pruning cites this paper.
Grounding-Aware Token Pruning: Recovering from Drastic Performance Drops in Visual Grounding Caused by Pruning Sparsity Meets Similarity: Leveraging Long-Tail Distribution for Dynamic Optimized Token Representation in Multimodal Large Language Models
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:22:37.891208Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 98e33e44-a5ab-4d3e-84c5-735d6adc56b6 · inbound
LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation cites this paper.
LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation Sparsity Meets Similarity: Leveraging Long-Tail Distribution for Dynamic Optimized Token Representation in Multimodal Large Language Models
Reference 71
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T12:46:04.838909Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.