{"as_of":"2026-08-15T13:50:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f10c6bd736cb4ffd8df17933f0dfb638927b5541ede622573ded20ed6900bb4d","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T23:21:41.816106Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T17:18:43.006113Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2405.02764","last_updated":"2024-09-12T22:18:03Z","snapshot_observed_at":"2026-08-14T01:54:01.842804Z","submitted_at":"2024-05-04T22:00:28Z","title":"Assessing Adversarial Robustness of Large Language Models: An Empirical Study","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.02764","snapshot_observed_at":"2026-08-10T23:21:41.816106Z","title":"Assessing adversarial robustness of large language models: An empirical study.arXiv preprint arXiv:2405.02764, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.00066","last_updated":"2025-06-07T11:27:26Z","snapshot_observed_at":"2026-08-14T11:24:12.417233Z","submitted_at":"2024-12-29T15:55:35Z","title":"On Adversarial Robustness of Language Models in Transfer Learning","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T23:21:41.816106Z"},"links":{"cited_paper":"/paper/2405.02764","citing_paper":"/paper/2501.00066"},"observation_digest":"sha256:ab29eb202aabd4b298d1535b3d6ebea7884e812496a78b66250e5a47437f40c3","observation_id":"5223ae79-5e8f-47b6-ab56-51e0d798337b","resolution":{"observed_at":"2026-08-10T23:21:41.816106Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02764","last_updated":"2024-09-12T22:18:03Z","snapshot_observed_at":"2026-08-14T01:54:01.842804Z","submitted_at":"2024-05-04T22:00:28Z","title":"Assessing Adversarial Robustness of Large Language Models: An Empirical Study","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.02764","snapshot_observed_at":"2026-08-06T17:40:06.404790Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.10330","last_updated":"2025-07-14T14:38:48Z","snapshot_observed_at":"2026-08-13T20:13:46.774840Z","submitted_at":"2025-07-14T14:38:48Z","title":"Bridging Robustness and Generalization Against Word Substitution Attacks in NLP via the Growth Bound Matrix Approach","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-06T17:40:06.404790Z"},"links":{"cited_paper":"/paper/2405.02764","citing_paper":"/paper/2507.10330"},"observation_digest":"sha256:f609980b105333c1b91731e88eaefd6756661e2ca4c3cf4c45a4e82b8330788e","observation_id":"c123b6c1-bcc2-421d-9762-3a31f5cce95e","resolution":{"observed_at":"2026-08-06T17:40:06.404790Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02764","last_updated":"2024-09-12T22:18:03Z","snapshot_observed_at":"2026-08-14T01:54:01.842804Z","submitted_at":"2024-05-04T22:00:28Z","title":"Assessing Adversarial Robustness of Large Language Models: An Empirical Study","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.02764","snapshot_observed_at":"2026-08-05T14:55:57.051121Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.20737","last_updated":"2025-08-28T13:00:28Z","snapshot_observed_at":"2026-08-07T08:32:18.705994Z","submitted_at":"2025-08-28T13:00:28Z","title":"Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-05T14:55:57.051121Z"},"links":{"cited_paper":"/paper/2405.02764","citing_paper":"/paper/2508.20737"},"observation_digest":"sha256:13a43fb578c4993adf4ba0166321558b20ad11d90a3406b68e17dcddcf8a2f91","observation_id":"a4f9dc18-43ee-4f7b-b31c-87e0b6741f14","resolution":{"observed_at":"2026-08-05T14:55:57.051121Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02764","last_updated":"2024-09-12T22:18:03Z","snapshot_observed_at":"2026-08-14T01:54:01.842804Z","submitted_at":"2024-05-04T22:00:28Z","title":"Assessing Adversarial Robustness of Large Language Models: An Empirical Study","version":2},"cited_work":{"arxiv_id":"2405.02764","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.02764","snapshot_observed_at":"2026-07-03T17:18:43.006113Z","title":"arXiv preprint arXiv:2405.02764 , year=","venue":null,"work_id":"cafac211-18c6-49a7-96ed-bdb53dfb5ccb","year":2024},"citing_paper":{"arxiv_id":"2605.04177","last_updated":"2026-05-05T18:14:59Z","snapshot_observed_at":"2026-08-11T00:38:13.651676Z","submitted_at":"2026-05-05T18:14:59Z","title":"Are LLMs Ready for Conflict Monitoring? Empirical Evidence from West Africa","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-05-08T17:48:51.792769Z"},"links":{"cited_paper":"/paper/2405.02764","citing_paper":"/paper/2605.04177"},"observation_digest":"sha256:0e1aa1ee762b18a37f81c8814f4482c7668001c4d6059f942d808ce864091754","observation_id":"6ff8606f-8ac0-4f89-ae67-29db416057dd","resolution":{"observed_at":"2026-05-11T17:11:18.047201Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02764","last_updated":"2024-09-12T22:18:03Z","snapshot_observed_at":"2026-08-14T01:54:01.842804Z","submitted_at":"2024-05-04T22:00:28Z","title":"Assessing Adversarial Robustness of Large Language Models: An Empirical Study","version":2},"cited_work":{"arxiv_id":"2405.02764","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.02764","snapshot_observed_at":"2026-07-03T17:18:43.006113Z","title":"arXiv preprint arXiv:2405.02764 , year=","venue":null,"work_id":"cafac211-18c6-49a7-96ed-bdb53dfb5ccb","year":2024},"citing_paper":{"arxiv_id":"2606.13439","last_updated":"2026-06-11T15:01:49Z","snapshot_observed_at":"2026-08-06T23:14:52.913167Z","submitted_at":"2026-06-11T15:01:49Z","title":"S-GBT: Smooth Growth Bound Tensor for Certified Robustness Against Word Substitution Attacks in NLP","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-27T07:09:20.940256Z"},"links":{"cited_paper":"/paper/2405.02764","citing_paper":"/paper/2606.13439"},"observation_digest":"sha256:e114d761035c9c68cc01819bfadb1ad70bb90425ed5b91017510b841176995c1","observation_id":"16596775-87ed-4adc-8d22-bf6c3497a0de","resolution":{"observed_at":"2026-07-03T14:08:22.542663Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02764","last_updated":"2024-09-12T22:18:03Z","snapshot_observed_at":"2026-08-14T01:54:01.842804Z","submitted_at":"2024-05-04T22:00:28Z","title":"Assessing Adversarial Robustness of Large Language Models: An Empirical Study","version":2},"cited_work":{"arxiv_id":"2405.02764","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.02764","snapshot_observed_at":"2026-07-03T17:18:43.006113Z","title":"arXiv preprint arXiv:2405.02764 , year=","venue":null,"work_id":"cafac211-18c6-49a7-96ed-bdb53dfb5ccb","year":2024},"citing_paper":{"arxiv_id":"2607.01800","last_updated":"2026-07-02T07:16:28Z","snapshot_observed_at":"2026-08-12T21:35:10.172334Z","submitted_at":"2026-07-02T07:16:28Z","title":"Do LLMs Truly Generalize in the Molecular Domain? A Perturbation-Based Analysis","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-03T17:16:44.993306Z"},"links":{"cited_paper":"/paper/2405.02764","citing_paper":"/paper/2607.01800"},"observation_digest":"sha256:6b848506557ac7d1e5e5285bd453a42adf26938a74a517c435cad288fa3740a7","observation_id":"64946a7b-adb2-4187-b3cf-18b1304a06a9","resolution":{"observed_at":"2026-07-03T17:18:43.007917Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2405.02764/citation-record","integrity":"/paper/2405.02764/integrity","json":"/paper/2405.02764/citation-record.json","paper":"/paper/2405.02764"},"outbound":[],"paper":{"arxiv_id":"2405.02764","last_updated":"2024-09-12T22:18:03Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-14T01:54:01.842804Z","submitted_at":"2024-05-04T22:00:28Z","title":"Assessing Adversarial Robustness of Large Language Models: An Empirical Study"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.02764."}