Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.15033.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:21:34.861100Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T22:22:38.192026Z
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 6b0e6642-c249-4dca-8626-087a0eddbcd1 · inbound
Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy cites this paper.
Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:21:34.861100Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 399bf6f5-25a4-4e1f-8613-2c2e36431556 · 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 SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:09:09.213401Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f131960-fa44-40a5-9d6e-9b4f5b04fd33 · 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 SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T22:22:38.253638Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.