{"as_of":"2026-08-14T15:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:154cade3bf21f561c040f16accb890dc10636d42e7f6b6d87c4e06e465d8e486","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:15:55.891940Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-10T01:36:44.042285Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-08-07T15:15:55.891940Z","title":"500xcompressor: Generalized prompt compression for large language models.arXiv preprint arXiv:2408.03094, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.15774","last_updated":"2025-05-21T17:26:11Z","snapshot_observed_at":"2026-08-09T17:14:36.713328Z","submitted_at":"2025-05-21T17:26:11Z","title":"Beyond Hard and Soft: Hybrid Context Compression for Balancing Local and Global Information Retention","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T15:15:55.891940Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2505.15774"},"observation_digest":"sha256:83f9ca50ff134438bc9cf91fa956fcdacf94f62dba62a25d4599d46ac7a7e3d6","observation_id":"12ea812d-cae2-4c03-b3b0-40a053fb60f9","resolution":{"observed_at":"2026-08-07T15:15:55.891940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-08-07T12:14:27.618067Z","title":"500xcompressor: Generalized prompt compression for large language models, 2024 b","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.00307","last_updated":"2025-08-20T23:19:57Z","snapshot_observed_at":"2026-08-13T15:06:03.268550Z","submitted_at":"2025-05-30T23:32:57Z","title":"Lossless Token Sequence Compression via Meta-Tokens","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T12:14:27.618067Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2506.00307"},"observation_digest":"sha256:44f0244f38a9e5d8167d82cbfdc1c683ab1b974c9ace375a383af9f80a161690","observation_id":"08a17c38-6d27-44a4-8d2e-13424f9efd05","resolution":{"observed_at":"2026-08-07T12:14:27.618067Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-08-07T04:09:25.403597Z","title":"500xcompressor: Generalized prompt compression for large language models.arXiv preprint arXiv:2408.03094, 2024b","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.11638","last_updated":"2025-06-13T10:11:01Z","snapshot_observed_at":"2026-08-14T08:05:44.396132Z","submitted_at":"2025-06-13T10:11:01Z","title":"LoRA-Gen: Specializing Large Language Model via Online LoRA Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T04:09:25.403597Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2506.11638"},"observation_digest":"sha256:7216128cae413d952a0136935a18b8080ba8a79be2aa384b7624d8b885bbf5bd","observation_id":"fa505fc0-417f-46cf-a035-2193ac830b73","resolution":{"observed_at":"2026-08-07T04:09:25.403597Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-08-06T21:18:47.996132Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.00715","last_updated":"2025-07-01T12:42:06Z","snapshot_observed_at":"2026-08-14T04:50:42.794210Z","submitted_at":"2025-07-01T12:42:06Z","title":"EARN: Efficient Inference Acceleration for LLM-based Generative Recommendation by Register Tokens","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T21:18:47.996132Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2507.00715"},"observation_digest":"sha256:32c94ad81c6187e868cf70e34b75e032c059cb2ac3e08706ed367cff82b4370b","observation_id":"46aac62e-036f-4d87-bbd6-517cd2ffb69b","resolution":{"observed_at":"2026-08-06T21:18:47.996132Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-08-06T19:17:30.088575Z","title":"acl-long.353","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.06085","last_updated":"2025-07-09T09:59:12Z","snapshot_observed_at":"2026-08-08T03:21:05.539346Z","submitted_at":"2025-07-08T15:24:27Z","title":"A Survey on Prompt Tuning","version":2},"reference_index":353,"source":"pdf_text","source_observed_at":"2026-08-06T19:17:30.088575Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2507.06085"},"observation_digest":"sha256:83e9ffb1600f10a83a23858b28de447e69c52e883e1d47c6d2f9b569f53907cf","observation_id":"e0061171-835e-4d88-ac35-9ccfcf50aa5e","resolution":{"observed_at":"2026-08-06T19:17:30.088575Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-08-04T11:23:50.377065Z","title":"500xcompressor: Generalized prompt compression for large language models.arXiv preprint arXiv:2408.03094,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.05363","last_updated":"2026-06-04T21:50:20Z","snapshot_observed_at":"2026-08-10T11:35:22.942093Z","submitted_at":"2025-10-06T20:41:43Z","title":"MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-04T11:23:50.377065Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2510.05363"},"observation_digest":"sha256:2cdfa52b3038d7cad031abe7db566668fa9c869cb5738a126a035fb1a422802f","observation_id":"7a2af889-0784-4c48-a3c4-4c9bbb59240f","resolution":{"observed_at":"2026-08-04T11:23:50.377065Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-08-04T08:06:11.689240Z","title":"500xcompressor: Generalized prompt compression for large language models.arXiv preprint arXiv:2408.03094, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2510.22963","last_updated":"2026-06-19T20:25:06Z","snapshot_observed_at":"2026-08-13T22:03:36.724770Z","submitted_at":"2025-10-27T03:37:41Z","title":"When Compression Becomes an Attack Surface: Black-Box Attacks on Prompt-Compressed LLM Agents","version":4},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-04T08:06:11.689240Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2510.22963"},"observation_digest":"sha256:1da268d5f4e6acfa4a15729fcdd0c731d6bea6000ab2c18f0d65f7d0a698542c","observation_id":"5e53419f-ea3f-41dc-96cc-933bfd93c206","resolution":{"observed_at":"2026-08-04T08:06:11.689240Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":"2408.03094","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-07-10T01:36:44.042285Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","venue":"cs.CL","work_id":"71c28b8c-7c7c-4f0c-9e12-f94b7e04b660","year":2024},"citing_paper":{"arxiv_id":"2604.13725","last_updated":"2026-04-15T11:00:17Z","snapshot_observed_at":"2026-08-12T13:44:52.295675Z","submitted_at":"2026-04-15T11:00:17Z","title":"On the Effectiveness of Context Compression for Repository-Level Tasks: An Empirical Investigation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-10T13:00:56.512868Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2604.13725"},"observation_digest":"sha256:b40142c06da5b42b7406e8e1d6fa0e92540801d923b945ff7dbfdea60b535561","observation_id":"6df78505-d6c7-4f7a-8048-57b6598a35c5","resolution":{"observed_at":"2026-05-10T13:40:27.556464Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":"2408.03094","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-07-10T01:36:44.042285Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","venue":"cs.CL","work_id":"71c28b8c-7c7c-4f0c-9e12-f94b7e04b660","year":2024},"citing_paper":{"arxiv_id":"2607.08032","last_updated":"2026-07-09T01:15:03Z","snapshot_observed_at":"2026-08-02T16:38:21.894642Z","submitted_at":"2026-07-09T01:15:03Z","title":"What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-07-10T01:26:59.421158Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2607.08032"},"observation_digest":"sha256:84ed7d7725b427237f639a14f32cf087ecfd9b0e120a9db09baa0d4b234fc469","observation_id":"dfa856b9-e5dc-424d-b4ce-8c02ed7b0902","resolution":{"observed_at":"2026-07-10T01:36:44.044034Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03094","snapshot_observed_at":"2026-08-01T23:14:55.032941Z","title":"Accepted ACL 2025 Main; University of Cambridge","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.15516","last_updated":"2026-07-17T00:03:47Z","snapshot_observed_at":"2026-08-09T04:50:07.964882Z","submitted_at":"2026-07-17T00:03:47Z","title":"Cache-Aware Prompt Compression:A Two-Tier Cost Model for LLM API Caching","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T23:14:55.032941Z"},"links":{"cited_paper":"/paper/2408.03094","citing_paper":"/paper/2607.15516"},"observation_digest":"sha256:e9b6748ff842df826aa0f70be84b9713dfc208705ffd0754ca335b039adfd25b","observation_id":"0a4b7d72-aae2-46c4-93b9-407f4c3e6bdf","resolution":{"observed_at":"2026-08-01T23:14:55.032941Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2408.03094/citation-record","integrity":"/paper/2408.03094/integrity","json":"/paper/2408.03094/citation-record.json","paper":"/paper/2408.03094"},"outbound":[],"paper":{"arxiv_id":"2408.03094","last_updated":"2024-08-06T10:51:47Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-12T23:07:53.010018Z","submitted_at":"2024-08-06T10:51:47Z","title":"500xCompressor: Generalized Prompt Compression for Large Language Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2408.03094."}