Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2412.01380.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T20:15:49.289390Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T13:21:35.626449Z
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 57e8b28b-7346-4cbf-9aca-f48e6a169591 · inbound
RAP: Runtime Adaptive Pruning for LLM Inference cites this paper.
RAP: Runtime Adaptive Pruning for LLM Inference Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T13:21:35.629058Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 244a3fa0-3f99-483d-b108-e6139357ad16 · inbound
Memory-Augmented Transformers: A Systematic Review from Neuroscience Principles to Enhanced Model Architectures cites this paper.
Memory-Augmented Transformers: A Systematic Review from Neuroscience Principles to Enhanced Model Architectures Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T20:15:49.289390Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b1490825-f9dd-4591-a84c-a20a207d8aab · inbound
AutoNeural: Co-Designing Vision-Language Models for NPU Inference cites this paper.
AutoNeural: Co-Designing Vision-Language Models for NPU Inference Efficient LLM Inference using Dynamic Input Pruning and Cache-Aware Masking
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T18:56:59.496372Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.