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Paper Citation Record · LEDGER

Prompt Compression for Large Language Models: A Survey

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2410.12388.

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

pith.paper-citation-record.v1
2410.12388 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:59:42.935313Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T01:36:43.999133Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
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  • 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 12bc833e-4df2-4f81-8b58-a3dbc5a63a37 · inbound

A Survey on Large Language Model Acceleration based on KV Cache Management cites this paper.

A Survey on Large Language Model Acceleration based on KV Cache Management Prompt Compression for Large Language Models: A Survey

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-11T00:38:46.737455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T00:38:46.737455Z digest=sha256:86cfc4312f77cd072f9f52d7c4a2978a529cd1e5592c78eae61060f00895c12b

Observation d09b3a46-b11d-4101-8ef1-9e0b10f9e519 · inbound

MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation cites this paper.

MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation Prompt Compression for Large Language Models: A Survey

Reference 31

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unresolved
no resolver link, observed 2026-08-10T22:56:53.726300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:56:53.726300Z digest=sha256:d676314fcf04124ed7cbbd56e90ec8abf7ead17fc0412dbe359c427f6cd2a1c9

Observation e8392a69-cc00-4091-b30d-6b8bb9197ce1 · inbound

ICPC: In-context Prompt Compression with Faster Inference cites this paper.

ICPC: In-context Prompt Compression with Faster Inference Prompt Compression for Large Language Models: A Survey

Reference 13

Resolution
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no resolver link, observed 2026-08-10T22:28:06.878755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:28:06.878755Z digest=sha256:4fb8341c797b07dc6527a8abce9b353e8e284b7732c655c93c117624182d2049

Observation d54c2f75-c0c5-492f-b9ff-7bd4c187271d · inbound

MOOSComp: Improving Lightweight Long-Context Compressor via Mitigating Over-Smoothing and Incorporating Outlier Scores cites this paper.

MOOSComp: Improving Lightweight Long-Context Compressor via Mitigating Over-Smoothing and Incorporating Outlier Scores Prompt Compression for Large Language Models: A Survey

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-16T10:59:42.935313Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:59:42.935313Z digest=sha256:9622dde7de00a572e68fd1c1dd91121f1e4f7f857e0ebca863882b559c005a72

Observation 9bca31e8-7d42-4bb8-8285-4e70d1aafaa3 · inbound

Hierarchical Document Refinement for Long-context Retrieval-augmented Generation cites this paper.

Hierarchical Document Refinement for Long-context Retrieval-augmented Generation Prompt Compression for Large Language Models: A Survey

Reference 33

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unresolved
no resolver link, observed 2026-08-15T21:15:57.980115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:15:57.980115Z digest=sha256:9cb38708c90bdeb1b25a029c312d2a42cf6e08302f3d4de93522163685037fcd

Observation dedcef3b-a145-4bef-8c36-514b5434f9e2 · inbound

Beyond Hard and Soft: Hybrid Context Compression for Balancing Local and Global Information Retention cites this paper.

Beyond Hard and Soft: Hybrid Context Compression for Balancing Local and Global Information Retention Prompt Compression for Large Language Models: A Survey

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T15:15:55.750442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:15:55.750442Z digest=sha256:2b23a24667c1881f290b5baedcef0a5db489c009ecaaf029ebba8018728dcac7

Observation ed4f9f04-76a1-4e96-8940-f9de2ac3c9cb · inbound

Lossless Token Sequence Compression via Meta-Tokens cites this paper.

Lossless Token Sequence Compression via Meta-Tokens Prompt Compression for Large Language Models: A Survey

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T12:14:27.469882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:14:27.469882Z digest=sha256:9ba7ff3a5c3f9efd6dc615a5fa293885ca4f2ec1aaf215fdf0db4909fa720eba

Observation bf15584c-e8d7-4b06-b85a-a95f762a0fa7 · inbound

The Future is Agentic: Definitions, Perspectives, and Open Challenges of Multi-Agent Recommender Systems cites this paper.

The Future is Agentic: Definitions, Perspectives, and Open Challenges of Multi-Agent Recommender Systems Prompt Compression for Large Language Models: A Survey

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T20:43:19.847504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:43:19.847504Z digest=sha256:2bb51ab139bc899e432972c734bcea5ac52972ca8c6e94fa7f5ccf8702b88e49

Observation faa9b5c3-f083-42d2-b206-e2fe136120eb · 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 Prompt Compression for Large Language Models: A Survey

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-04T08:06:11.609545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T08:06:11.609545Z digest=sha256:cb496b7629daa6b824053b03262793d4037c8f3031017b2a08cd2f9df501c2fe

Observation 3d45045c-c8ba-4fd7-be67-fd3ea66d46f3 · inbound

SkillReducer: Optimizing LLM Agent Skills for Token Efficiency cites this paper.

SkillReducer: Optimizing LLM Agent Skills for Token Efficiency Prompt Compression for Large Language Models: A Survey

Reference 23

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unresolved
no resolver link, observed 2026-07-13T15:31:30.563780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T15:31:30.563780Z digest=sha256:e6f47e20410a7c3428ef71af72261cefffe328c23a6b94ce324adcae4e69e9fa

Observation f3789679-6d54-4609-a5a4-d3fa064edd84 · inbound

Layer-wise Token Compression for Efficient Document Reranking cites this paper.

Layer-wise Token Compression for Efficient Document Reranking Prompt Compression for Large Language Models: A Survey

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-21T03:03:55.846477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-21T03:02:34.320850Z digest=sha256:338abcbacc2891ab58f5bd104a83fe2109916982c7e2f41f52feb6f2cc3ef53d

Observation 116eca11-66d6-48e7-9272-d5fa02d27726 · inbound

Layer-wise Token Compression for Efficient Document Reranking cites this paper.

Layer-wise Token Compression for Efficient Document Reranking Prompt Compression for Large Language Models: A Survey

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:21:21.664017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-22T09:18:39.895672Z digest=sha256:61384bdb827c947cad3799d106ce50f996d3f2343618ec1c363c3cc30c52b181

Observation 9048ecd7-f98f-4a57-8267-382e2e46f0bf · inbound

Mem-$\pi$: Adaptive Memory through Learning When and What to Generate cites this paper.

Mem-$\pi$: Adaptive Memory through Learning When and What to Generate Prompt Compression for Large Language Models: A Survey

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-21T04:29:34.605265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-21T04:27:25.041652Z digest=sha256:d61fef6dcba7498bf5d1a809763f91b822d470255538eb22f91dc73aae16643c

Observation 13e60dc3-f1a7-4b68-bc52-1385b0fc11ec · inbound

Less is More: Lightweight Prompt Compression for Question Answering Applications on Edge Devices cites this paper.

Less is More: Lightweight Prompt Compression for Question Answering Applications on Edge Devices Prompt Compression for Large Language Models: A Survey

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:55:34.917339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-01T08:49:28.538659Z digest=sha256:a49cda00bf41fe5d2b504ea2f90db068abead41243701311629d1d45f5903b2f

Observation 43718fd4-1413-4e94-80a7-01c4610678e2 · inbound

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL cites this paper.

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL Prompt Compression for Large Language Models: A Survey

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-01T09:45:40.243404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-01T06:13:54.960194Z digest=sha256:c794f95a28a35f651cd71dc76772179a79300947db89e69c7c986560405e0ea6

Observation 999ecfde-2902-47e8-b206-7e65b49975ae · inbound

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL cites this paper.

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL Prompt Compression for Large Language Models: A Survey

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-13T07:12:34.663753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T07:12:34.663753Z digest=sha256:1e70f08390fe2d41637c2c469487a024cbc19fe3c7d603612d129dd1765fca29

Observation cde44830-d633-47e1-9f64-1fb457c6b837 · inbound

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL cites this paper.

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL Prompt Compression for Large Language Models: A Survey

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-02T09:17:12.944536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:17:12.944536Z digest=sha256:10d250331e7e77375bb8b4aa7709c925731a198a5e7fef8061af1d0c91ff261d

Observation cb6cd177-d0e6-4b66-a2bf-5cc7c1334c7c · inbound

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL cites this paper.

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL Prompt Compression for Large Language Models: A Survey

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-03T02:05:45.179391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T02:05:45.179391Z digest=sha256:f06ffef751d163a399d5722387ae21462bd9278c61a172ef7c4ac62de190df9d

Observation 8e792e00-37db-424f-bdbf-a6676f03ee16 · inbound

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL cites this paper.

ECHO: Prune To Act, Trace To Learn With Selective Turn Memory In Agentic RL Prompt Compression for Large Language Models: A Survey

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-04T04:36:25.556693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:36:25.556693Z digest=sha256:3eea12256516d27c748a1db11686f8174f7ca242eb6635e566a0bfc350fd7aa3

Observation 02b5f9ab-55f3-40c3-9680-7ebccbf4e6ce · 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 Prompt Compression for Large Language Models: A Survey

Reference 66

Resolution
verified exact
local_arxiv, observed 2026-07-10T01:36:44.000268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-07-10T01:26:59.421158Z digest=sha256:8f56c7d0c06fe058e33e17366c3b948c2bf780f914ae70056eafcd5c61b4334f

Observation 92b9ae54-77a5-4c4a-b4a6-6c7cdfb34616 · inbound

AI Agents Do Not Fail Alone:The Context Fails First cites this paper.

AI Agents Do Not Fail Alone:The Context Fails First Prompt Compression for Large Language Models: A Survey

Reference 9

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no resolver link, observed 2026-08-02T02:38:47.039965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T02:38:47.039965Z digest=sha256:343ddc06b154c0eecc6cfb294db278b3b39da62c3378b3495ca4f49b8e3602ab

Observation dbcdebf8-8dac-41d6-99aa-bd40e39b870d · inbound

VoxZip: Semantic-Anchored Temporal KV Cache Compression for Long-Context Audio Inference cites this paper.

VoxZip: Semantic-Anchored Temporal KV Cache Compression for Long-Context Audio Inference Prompt Compression for Large Language Models: A Survey

Reference 18

Resolution
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no resolver link, observed 2026-08-14T04:35:59.645686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:35:59.645686Z digest=sha256:f2ec801cbe147026629f656f5b6a6f6393403365d20a6f9ab698256e353b6cbe