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Paper Citation Record · LEDGER

CompAct: Compressing Retrieved Documents Actively for Question Answering

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2407.09014.

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

pith.paper-citation-record.v1
2407.09014 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:59:44.836577Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T01:36:44.317798Z

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 e16488d5-e3c3-4409-86ab-23844b81acac · inbound

Boosting Long-Context Management via Query-Guided Activation Refilling cites this paper.

Boosting Long-Context Management via Query-Guided Activation Refilling CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T14:07:31.251479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:07:31.251479Z digest=sha256:4e8c780513da730701f46383060195432d2aa5ecd4a0a5630cac936dc4705537

Observation 23172091-3e84-4033-bc60-768a694c016d · inbound

Provence: efficient and robust context pruning for retrieval-augmented generation cites this paper.

Provence: efficient and robust context pruning for retrieval-augmented generation CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T13:43:43.874930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:43:43.874930Z digest=sha256:4b248b974b6bcc8f7b05c7de678537de295f9bb99085ae723978a40db3561859

Observation 5ada8d60-cc5d-4f3e-ba47-5f186fd3f410 · inbound

Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Tasks cites this paper.

Smooth Reading: Bridging the Gap of Recurrent LLM to Self-Attention LLM on Long-Context Tasks CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T17:59:44.836577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:59:44.836577Z digest=sha256:3d3e1bf2269240d31d4bb8a85ff8b1f568fe5d2a83b8a9048127d2163938bcb1

Observation 6ad74512-0325-439d-8494-0337a87ded2a · 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 CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-04T11:23:52.610520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:23:52.610520Z digest=sha256:ab512c94ac614dbf21d995810327168b93c41a0652bd618a35fbb3b61d78e678

Observation 08254568-ecd6-4962-80ad-ab89b61007f0 · inbound

Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression cites this paper.

Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-21T13:44:11.401550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-21T13:43:51.127429Z digest=sha256:36e99f877e1f010414c389dc2ac6bf7f77dfe61a116a53ffa15e9405a223d4ce

Observation a087667f-21cd-453c-814c-2c39eca4adb7 · inbound

Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression cites this paper.

Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-03T03:25:23.118918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:25:23.118918Z digest=sha256:bf971440d0809dab1a155fd7705aad0e25a2c86f2f6d110076eab60fbc1b8543

Observation de10d316-eedc-4037-bdde-00262c42ff5d · inbound

Prism-Reranker: Beyond Relevance Scoring -- Jointly Producing Contributions and Evidence for Agentic Retrieval cites this paper.

Prism-Reranker: Beyond Relevance Scoring -- Jointly Producing Contributions and Evidence for Agentic Retrieval CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:31:15.676452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-08T05:16:19.037595Z digest=sha256:d1d19bc2c721a6244015da7b836416a1f7d2c3705ef972bb946531fb51bc8f1f

Observation 02efc666-2ef4-4ae5-9b3c-3d9c6ede785e · inbound

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

End-to-End Context Compression at Scale CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 90

Resolution
verified exact
arxiv_id, observed 2026-07-03T01:17:31.566471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-27T16:36:54.699174Z digest=sha256:21a16c896851ba6e1f32bd90ec7c2d7b7ddf7c0488cf5e68c74aa3480a0ad772

Observation ee86d1fb-204e-4c23-afee-fd35d59f9116 · inbound

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair cites this paper.

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:18:22.597036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-03T14:09:32.980488Z digest=sha256:11ad8572c96e8f9e7e02d252c3874812d0f0a81acd969394ed8f801ae95fed0e

Observation 71a550e0-3802-41c3-bf65-231f060cd36d · inbound

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair cites this paper.

ContextSniper: AntTrail's Token-Efficient Code Memory for Repository-Level Program Repair CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 26

Resolution
unresolved
no resolver link, observed 2026-07-12T08:32:14.868469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:32:14.868469Z digest=sha256:41b675df81e7334abe505060ca6534696f5e902d936abaa72f2d3b4e8a154a66

Observation 62a601d2-500d-43cb-af12-5c5c62bbb557 · inbound

What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents cites this paper.

What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents CompAct: Compressing Retrieved Documents Actively for Question Answering

Reference 144

Resolution
verified exact
local_arxiv, observed 2026-07-10T01:36:44.318895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-10T01:26:59.421158Z digest=sha256:a08a746b9fb6272f7509724de4be6ee1f001e2b0fa93d7dd811a8865ecdfecb8