Paper Citation Record · LEDGER

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains

As of 8 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2508.19357.

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

pith.paper-citation-record.v1
2508.19357 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:50:52.203226Z

measured 30 of 30 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T12:31:41.148624Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T07:59:39.522539Z

Reference resolution

29 of 29 outbound references displayed

verified exact2
verified fuzzy24
unresolved3
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6091000c-9ced-4b45-bb23-b3171ae6f8e8 · outbound

This paper cites A survey on large language model (LLM) security and privacy: The good, the bad, and the ugly,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains A survey on large language model (LLM) security and privacy: The good, the bad, and the ugly,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.841676Z

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.

Observation e8458bc9-236a-4ec7-8cdf-ddef8036d7fd · outbound

This paper cites A survey on large language model (llm) security and privacy: The good, the bad, and the ugly,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains A survey on large language model (llm) security and privacy: The good, the bad, and the ugly,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.825741Z

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.

Observation 40cde065-16d2-417d-9aba-a8280ab5b641 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Retrieval-augmented generation for knowledge-intensive NLP tasks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.810086Z

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.

Observation 36d1dd18-67f2-4562-a6b9-e6f0d9573f80 · outbound

This paper cites Using an LLM to help with code understanding,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Using an LLM to help with code understanding,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.794455Z

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.

Observation af7dcd49-aa68-4c6f-8248-e2fdcaf4de61 · outbound

This paper cites RECOMP: improving retrieval-augmented lms with context compression and selective augmentation,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains RECOMP: improving retrieval-augmented lms with context compression and selective augmentation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.778604Z

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.

Observation 301dc3dc-f40f-43a1-a97e-cdea1778e9eb · outbound

This paper cites Llmlingua: Compress- ing prompts for accelerated inference of large language models,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Llmlingua: Compress- ing prompts for accelerated inference of large language models,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.763714Z

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.

Observation 4daa5838-ba2b-4b46-9806-a8445a591362 · outbound

This paper cites Retrieval-augmented generation for ai-generated content: A survey,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Retrieval-augmented generation for ai-generated content: A survey,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.748084Z

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.

Observation eda63b9e-d732-4579-a709-a3ac2634473f · outbound

This paper cites Retrieval augmented generation (RAG) and beyond: A comprehensive survey on how to make your llms use external data more wisely,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Retrieval augmented generation (RAG) and beyond: A comprehensive survey on how to make your llms use external data more wisely,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.731940Z

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.

Observation 8c71b708-461a-444d-a270-2d5e73f2aaee · outbound

This paper cites Agentic retrieval- augmented generation: A survey on agentic RAG,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Agentic retrieval- augmented generation: A survey on agentic RAG,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.714951Z

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.

Observation 68058711-2fb6-43f5-a205-2c8c7735db61 · outbound

This paper cites Lambda: A large model based data agent,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Lambda: A large model based data agent,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.696087Z

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.

Observation acf46770-278f-4b23-9568-bc23bf6a2bd7 · outbound

This paper cites A survey on large language model-based agents for statistics and data science,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains A survey on large language model-based agents for statistics and data science,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T15:50:52.116169Z

Source-reported events for the cited work

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Observation bdeb3e3f-ae27-48d7-b2b1-638b7fa4eff0 · outbound

This paper cites OG-RAG: ontology-grounded retrieval-augmented generation for large language models,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains OG-RAG: ontology-grounded retrieval-augmented generation for large language models,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.676947Z

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.

Observation 553acec6-bb5a-45cf-9e95-bee48584935d · outbound

This paper cites Improving the domain adaptation of retrieval aug- mented generation (RAG) models for open domain question answering,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Improving the domain adaptation of retrieval aug- mented generation (RAG) models for open domain question answering,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.659182Z

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.

Observation d85c2d30-1b80-44bb-9636-14a28bcf679a · outbound

This paper cites Blended RAG: improving RAG (retriever-augmented generation) accuracy with semantic search and hybrid query-based retrievers,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Blended RAG: improving RAG (retriever-augmented generation) accuracy with semantic search and hybrid query-based retrievers,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.641434Z

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.

Observation 7b747d76-40cf-4d95-8b16-e06388277b70 · outbound

This paper cites Face4rag: Factual consistency evaluation for retrieval augmented generation in chinese,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Face4rag: Factual consistency evaluation for retrieval augmented generation in chinese,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.624067Z

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.

Observation 8e1153dd-d65b-47d7-a1ff-2f6c776e720b · outbound

This paper cites Hoprag: Multi-hop reasoning for logic-aware retrieval-augmented gen- eration,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Hoprag: Multi-hop reasoning for logic-aware retrieval-augmented gen- eration,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.606995Z

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.

Observation 4e170a4a-2437-4a1c-a3ff-6f0c1cee9bec · outbound

This paper cites MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-05T15:50:52.145593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efb11ba4-5c86-4273-ad51-3d9e39c38ad3 · outbound

This paper cites LlamaCare: A Large Medical Language Model for Enhancing Healthcare Knowledge Sharing.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains LlamaCare: A Large Medical Language Model for Enhancing Healthcare Knowledge Sharing

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-05T15:50:52.298986Z

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.

Observation 0108b316-e2f7-467e-9941-006e4f6e15f7 · outbound

This paper cites Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T15:50:52.155944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 671ee8a9-5fb3-4ed1-9caf-a67b08494c46 · outbound

This paper cites Visual in-context learning for large vision-language models,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Visual in-context learning for large vision-language models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.590884Z

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.

Observation 4d19f740-83c0-4ccc-8c77-eda7098c063a · outbound

This paper cites Reasoning or Not? A Comprehensive Evaluation of Reasoning LLMs for Dialogue Summarization.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Reasoning or Not? A Comprehensive Evaluation of Reasoning LLMs for Dialogue Summarization

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-05T15:50:52.255189Z

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.

Observation 95d5a439-561b-4a2e-b9c2-78b5cc54491f · outbound

This paper cites Adapting llms for efficient context processing through soft prompt compression,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Adapting llms for efficient context processing through soft prompt compression,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.574544Z

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.

Observation 19331763-14d8-46e3-bb1a-a1e6f3b8f5c3 · outbound

This paper cites Do multi- document summarization models Synthesize?.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Do multi- document summarization models Synthesize?

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.558252Z

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.

Observation b5632ee2-caf4-44de-8228-1737ff47398f · outbound

This paper cites Llm-based mofs synthesis condition extraction using few- shot demonstrations,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Llm-based mofs synthesis condition extraction using few- shot demonstrations,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.541110Z

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.

Observation 098a392f-f0ae-4aa2-8dd5-2bebff151641 · outbound

This paper cites Leancontext: Cost- efficient domain-specific question answering using llms,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Leancontext: Cost- efficient domain-specific question answering using llms,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.519639Z

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.

Observation a00bec48-3084-4fb9-b9cf-35284bcb6381 · outbound

This paper cites Hlspilot: Llm-based high- level synthesis,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Hlspilot: Llm-based high- level synthesis,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.499504Z

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.

Observation 25e963b8-5843-441d-8d37-c006cd116b8d · outbound

This paper cites Sagallm: Context management, validation, and transaction guarantees for multi-agent LLM planning,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Sagallm: Context management, validation, and transaction guarantees for multi-agent LLM planning,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.483140Z

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.

Observation 19f7cee7-ea90-42c6-ac11-482fa7b6a17f · outbound

This paper cites HYSYNTH: context-free LLM approximation for guid- ing program synthesis,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains HYSYNTH: context-free LLM approximation for guid- ing program synthesis,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.466476Z

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.

Observation 877af04f-a76c-4d6b-8114-6f5296b4fc89 · outbound

This paper cites Knowledge distillation and dataset distillation of large language models: Emerging trends, challenges, and future directions,.

Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains Knowledge distillation and dataset distillation of large language models: Emerging trends, challenges, and future directions,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T15:50:52.448355Z

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.

Pith citing papers

Observation 518d203d-ceb8-421b-a1f3-fde51c921c7a · inbound

Fixed RAG Compression Collapses Measured Reader Scaling cites this paper.

Fixed RAG Compression Collapses Measured Reader Scaling Context-Adaptive Synthesis and Compression for Enhanced Retrieval-Augmented Generation in Complex Domains

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-04T07:59:39.524294Z

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.