Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Perception Compressor: A Training-Free Prompt Compression Framework in Long Context Scenarios
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.19272.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:05:54.223208Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-16T11:05:54.431309Z
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 50229fa5-679d-4481-b1c0-3e014e99f980 · inbound
PIS: Linking Importance Sampling and Attention Mechanisms for Efficient Prompt Compression cites this paper.
PIS: Linking Importance Sampling and Attention Mechanisms for Efficient Prompt Compression Perception Compressor: A Training-Free Prompt Compression Framework in Long Context Scenarios
Reference 37
- Resolution
- verified exact
- local_arxiv, observed 2026-08-16T11:05:54.436671Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 7b2c99fd-c725-4189-b5c0-8c555909652c · inbound
MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts cites this paper.
MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts Perception Compressor: A Training-Free Prompt Compression Framework in Long Context Scenarios
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T11:23:51.842797Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.