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Paper Citation Record · LEDGER

Learning to Compress Prompt in Natural Language Formats

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.18700.

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

pith.paper-citation-record.v1
2402.18700 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:04:27.770008Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T01:27:30.488955Z

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 ed9ed8bf-438e-478a-80a1-8b0b755002a4 · inbound

Cartridges: Lightweight and general-purpose long context representations via self-study cites this paper.

Cartridges: Lightweight and general-purpose long context representations via self-study Learning to Compress Prompt in Natural Language Formats

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T06:04:27.770008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:04:27.770008Z digest=sha256:72bc1ed3c4166a58de01b71dfe51b5c561aa51f6c324842f0c6c0404b1196a4c

Observation cd2b4d1b-d958-41f7-bbaa-e77f061bec9a · inbound

Not All Errors Are Created Equal: ASCoT Addresses Late-Stage Fragility in Efficient LLM Reasoning cites this paper.

Not All Errors Are Created Equal: ASCoT Addresses Late-Stage Fragility in Efficient LLM Reasoning Learning to Compress Prompt in Natural Language Formats

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T23:32:54.984357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:32:54.984357Z digest=sha256:50e226d64f9a2ee223b4895519dbd0af287d09c65ec9e7f13690e8f4db07ca1b

Observation 7e717e9b-2d04-4c44-8527-7fbc7807a1fe · inbound

When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents cites this paper.

When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents Learning to Compress Prompt in Natural Language Formats

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-04T08:06:09.749848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:06:09.749848Z digest=sha256:d142e5074fb4e132892a0f5f678d33357af85b5e6ba822d6482fb3d1a0a453f8

Observation 1b80102e-3443-455d-b7ed-d6eae8a1e7a6 · inbound

Token Sparse Attention: Efficient Long-Context Inference with Interleaved Token Selection cites this paper.

Token Sparse Attention: Efficient Long-Context Inference with Interleaved Token Selection Learning to Compress Prompt in Natural Language Formats

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-03T05:09:28.199967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T05:09:28.199967Z digest=sha256:9a7a62721ff8a8382a8c3ca11d74a2a6f3eac150223651721506dd986eb722e1

Observation 329c8287-f183-4e3d-a00f-7975feb22fc2 · inbound

Post Reasoning: Improving the Performance of Non-Thinking Models at No Cost cites this paper.

Post Reasoning: Improving the Performance of Non-Thinking Models at No Cost Learning to Compress Prompt in Natural Language Formats

Reference 85

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:06:09.534412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-08T10:19:08.451445Z digest=sha256:a02c0ebfd0ff0738c449a2571eb3ce962219267abb5ee08171e218c8f4072b1e

Observation 25ae6683-a46e-4ccd-a496-90bdd659825e · inbound

End-to-End Context Compression at Scale cites this paper.

End-to-End Context Compression at Scale Learning to Compress Prompt in Natural Language Formats

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T01:27:30.490629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T16:36:54.699174Z digest=sha256:f9ea593eb2f090f6e827d2618946be2222a370beb5b37920ea314fae2808a6e6