{"as_of":"2026-08-21T03:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4f225e05f4b088e1d11edde98fb6dd30b652e7fd0187c67f1bf1a9e20bb84610","coverage":[{"denominator":52,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":52,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:51:32.338793Z","state":"measured"},{"denominator":52,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":52,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2505.20866/citation-record","integrity":"/paper/2505.20866/integrity","json":"/paper/2505.20866/citation-record.json","paper":"/paper/2505.20866"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:44.230814Z","title":"Deep learning for encrypted traffic classification: An overview,","venue":null,"work_id":"4cc97396-a613-40e4-9d1d-53c99109ea72","year":2019},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:26.404295Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:3b1b5fa4b88fe6d24c165fa164b4c61a5ef830bce7374335c123c3d8d8b6ced1","observation_id":"298a38dd-6a69-409b-824c-1086ece55efd","resolution":{"observed_at":"2026-08-07T13:51:44.353969Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:44.021127Z","title":"Realtime robust malicious traffic detection via frequency domain analysis,","venue":null,"work_id":"8d20b610-b440-4b24-afe9-4fa8677322a8","year":2021},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:26.514170Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:1155c64ff6a9502d96f162ae11bc97784f1b735e22766f5becb94f09046ba0e5","observation_id":"bc6989a4-8e3f-4c63-8c4c-5f781c2d0f8b","resolution":{"observed_at":"2026-08-07T13:51:44.127504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:43.697812Z","title":"An in- depth study of microservice call graph and runtime performance,","venue":null,"work_id":"4c6cb695-f001-48a7-8507-b9cd3f3cfec6","year":2022},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:26.605331Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:04c8b577b4c66de6472c3fefd230f27c414a0971547fa292ef40b664bd83b26a","observation_id":"1b95885c-7287-4d5d-849b-33c52e9e7f0c","resolution":{"observed_at":"2026-08-07T13:51:43.819966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:43.508821Z","title":"Multi-tier workload consolidations in the cloud: Profiling, modeling and optimization,","venue":null,"work_id":"a2ac42d4-0148-43b8-abaf-d5d31a64e045","year":2022},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:26.712071Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:d6b556b454f889e59cd89af8deb4af5912a02c5f0312ea12182e6d752e6de56d","observation_id":"74c4965d-558e-4992-96f7-150111d449be","resolution":{"observed_at":"2026-08-07T13:51:43.611194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:43.253763Z","title":"& Wang, Y","venue":null,"work_id":"99fcc985-8d34-4162-8e03-e4fc142770e8","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:26.786605Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:46c0c3ad86625e279020966fd65bd2a510a0e834b8ce82e8690328a1688d5c72","observation_id":"969f6e41-e60b-4eee-a171-4207ed22bb11","resolution":{"observed_at":"2026-08-07T13:51:43.374620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:43.062810Z","title":"Machine learning for encrypted malware traffic classification: Accounting for noisy labels and non- stationarity,","venue":null,"work_id":"cec5ed10-e1a6-4acb-ac10-9514d3dbc8b0","year":2017},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:26.901177Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:52d0bbaa72c2d6defbbd7316329f08ff6456759b61d5338a1fbb88f17a06010e","observation_id":"51a72dad-3cf1-43f1-8fe6-e7c3e87a3889","resolution":{"observed_at":"2026-08-07T13:51:43.115009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:42.861550Z","title":null,"venue":null,"work_id":"ac1b177e-8dfd-405c-a250-b3e35c0660f1","year":2021},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:27.010333Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:d43207a3d0890aee0937998592e367ba347d383c94adcbdbdfe3d9aa52a33f9c","observation_id":"d67c3e20-cc40-45b2-a177-0db398e4fe43","resolution":{"observed_at":"2026-08-07T13:51:42.909613Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:42.678767Z","title":null,"venue":null,"work_id":"a93b3009-ab45-4f67-86af-838b12f63fd5","year":2018},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:27.109921Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:a549939255082aee546b7376891e8707cabf8bade51f2fd05365abe5ff7238a5","observation_id":"5e283412-73ba-4617-be98-aac1ea156d2d","resolution":{"observed_at":"2026-08-07T13:51:42.770276Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:42.320601Z","title":"& Grundy, J","venue":null,"work_id":"a1f69072-0d20-4d75-bfa5-3fac53ce23ec","year":2021},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:27.350582Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:dcb32d4899d82aba9bd7c8f49673638930334e1e5e354392449f78c28deac096","observation_id":"4a970361-693b-4ff1-b82c-0e1df7d79192","resolution":{"observed_at":"2026-08-07T13:51:42.425080Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:42.112043Z","title":"& Tuffin, B","venue":null,"work_id":"e4bccbf0-2527-4b18-8b3d-8f0c466f6ec3","year":2017},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:27.438562Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:34f9a817144aa6896ddd5399afb1ff5ca0ea011dea58dfd27eac10240707ae44","observation_id":"cc1a5bfa-00d8-4841-802f-fc8d2d8ea58a","resolution":{"observed_at":"2026-08-07T13:51:42.195657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:41.949412Z","title":"Mobile cdn market — global industry report","venue":null,"work_id":"3eb5c168-ca90-453e-8504-df7e0b8252a4","year":2020},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:27.647140Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:60ba43f334905f3f3bd1d80c0271d6b5d7bc5086da2637577f94592ff9300a4d","observation_id":"fe5bd49b-aa2d-46e7-bcc8-2f8a3c3f1032","resolution":{"observed_at":"2026-08-07T13:51:42.012426Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:41.750953Z","title":"ET-BERT: A contextualized datagram representation with pre-training transformers for encrypted traffic classification,","venue":null,"work_id":"2f732b96-8105-414f-b322-aed289c0c514","year":2022},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:27.773073Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:f9cf8b9895b73c14000c320cc2222441ce2f7753942f6654e122a9cfe40b819d","observation_id":"7df409a2-cc6c-4252-946b-eb1fc978de0c","resolution":{"observed_at":"2026-08-07T13:51:41.826743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:41.510429Z","title":null,"venue":null,"work_id":"761f9306-e907-4bf6-95cc-58e5607652d0","year":2025},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:27.883576Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:e6cc37b9f5921cf4c7bf85d1f20ac21389c624aa12244d3a024565317b96599f","observation_id":"7c1a22ec-864f-4ea3-9b9c-a572bc3b0f0c","resolution":{"observed_at":"2026-08-07T13:51:41.584381Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:41.320840Z","title":"& Joosen, W","venue":null,"work_id":"df0e8308-6186-4246-b784-65c26af03c2e","year":2018},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:28.047340Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:6b6f1b9df4ba93951e4471bd65da4ecc6b305cf44c68fcfaced512928c0f79f0","observation_id":"bc45c57f-c1e0-4238-8fd9-55b48b405b52","resolution":{"observed_at":"2026-08-07T13:51:41.406709Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:41.107464Z","title":"Website fingerprinting at internet scale,","venue":null,"work_id":"3c3f4406-4fa9-4b09-81ec-c0d6e7927c56","year":2016},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:28.149343Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:e9bc7fadef05734436973cf908fa51449750a0012b5b79e8c65a2a13f5924fbe","observation_id":"3424d8ce-c6bc-409a-81c2-bc1d67401e7c","resolution":{"observed_at":"2026-08-07T13:51:41.207316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:40.909172Z","title":"& Zhang, Y","venue":null,"work_id":"1c9ce11e-5db9-4ea2-b0bf-d9f6d7566e91","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:28.280679Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:094d70717fe58f90c7b5aa6886ff19987a88e555e3f424cd7ce031eb20038d42","observation_id":"54ac2fb2-9372-4af4-aba5-d37e7224f7cf","resolution":{"observed_at":"2026-08-07T13:51:41.028531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:40.529418Z","title":"& Ananiadou, S","venue":null,"work_id":"959a893a-a897-4802-bac7-8565e9516809","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:28.525143Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:c6616d31a421ecff467c6b14e80e8fe025a4960c097a6a432ca60221036995fb","observation_id":"fb728c3d-1635-4c5d-964b-9b245073d150","resolution":{"observed_at":"2026-08-07T13:51:40.587111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:40.322830Z","title":"TSCRNN: A novel classification scheme of encrypted traffic based on flow spatiotemporal features for efficient management of iiot,","venue":null,"work_id":"d03ca902-b5b5-4a64-ae5b-36f0e64f0dc5","year":2021},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:28.660377Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:4d0c085f6e4fab8f7616b76ef1ee72acfc5a9222713b5679112b139f561b5581","observation_id":"4d3f0ddd-cbaf-4ed1-a37b-d0624dccbc50","resolution":{"observed_at":"2026-08-07T13:51:40.417623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:42.519490Z","title":"1928-1943 (2018)","venue":null,"work_id":"bb2b3fdd-c8a0-4153-9e60-e2022fa9cba1","year":2018},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:27.247229Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:06f329618cf097ff7e6de56148fecf46f4e3b3e8cf9a5b68370edb8cb50cf74e","observation_id":"24bcde26-10b8-4fd1-95bd-650fde871d71","resolution":{"observed_at":"2026-08-07T13:51:42.603083Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:39.905555Z","title":"Malware traffic classification using convolutional neural network for representation learning,","venue":null,"work_id":"b5758347-6a71-4069-ad9c-f168d4b7184a","year":2017},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:28.884868Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:c74f897f77e5b4a41a7592d0399b85a9c2249778f06d04000d203e3f860a98f8","observation_id":"999988bb-77a7-4963-a913-cf4447381514","resolution":{"observed_at":"2026-08-07T13:51:39.986789Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:40.154923Z","title":"Deep packet: a novel approach for encrypted traffic classification using deep learning,","venue":null,"work_id":"26a3dd23-0ea9-4a3d-8caa-b3218c4bea87","year":1999},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:28.757632Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:2f4d3b210422c57a8fb20dc337fd9277799d10dfa510c84de4878f3b4657f78f","observation_id":"118e4ae5-78a9-4924-b5b5-0edd3904c1c7","resolution":{"observed_at":"2026-08-07T13:51:40.218122Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:29.136429Z","title":"Fs-net: A flow sequence network for encrypted traffic classification,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:29.136429Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:883fb9414f2d1ea6fb44472abcdb68e945076b9adea75e4a05d84d9b30b01a97","observation_id":"f50993b0-60a6-405c-ae7d-60d3a23d2957","resolution":{"observed_at":"2026-08-07T13:51:29.136429Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:39.743064Z","title":"& Fedus, W","venue":null,"work_id":"03119a9d-48de-4a36-98bb-899b7efe9a2a","year":2022},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:29.023872Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:44019422beea0763be1409cc4e27ea879daf674c579a910f911142ed51fe0a00","observation_id":"c2656954-fde7-4464-be84-71ab767b5415","resolution":{"observed_at":"2026-08-07T13:51:39.806124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:39.100597Z","title":"PERT: payload encoding representation from transformer for encrypted traffic classification,","venue":null,"work_id":"e824cee1-03e4-4371-b65d-945915079d39","year":2020},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:29.386912Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:c32d1f7dda4de891e2ebec37d88255b114625e5e34d4cf1151eb2492950abec2","observation_id":"350165f8-fdc6-4c6c-be61-7b7322b03203","resolution":{"observed_at":"2026-08-07T13:51:39.258282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:39.490807Z","title":"& Konan, M","venue":null,"work_id":"0f4d6782-259e-497a-9105-ea869e59fb99","year":2017},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:29.258329Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:5e909b6ecad23e9adc926b2ffc8ff3bc1fd8d09e5ccfd6f50d9f018e77ecfe32","observation_id":"c15d353b-0f14-45a3-a6b0-f22218b499a0","resolution":{"observed_at":"2026-08-07T13:51:39.646859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:38.372753Z","title":"& Huang, C","venue":null,"work_id":"286d529a-9ebd-4abc-b469-09ef23e200ee","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:29.675103Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:6d95be4c16399380f3f97b5e44c0822f9fa2de2fc1223ecbb74567963a579d1d","observation_id":"befd6c6b-f3bf-4af1-b167-c1a38c3f6d81","resolution":{"observed_at":"2026-08-07T13:51:38.500650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:38.678722Z","title":"Unbiased look at dataset bias,","venue":null,"work_id":"38ea850a-de34-43f4-8cdd-127f78453d8f","year":2011},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:29.533097Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:31dcb54c5ead1b6c5ff7c5c2e8a75840da42687dbab6e5d196af168fd72d4997","observation_id":"bed70017-3c05-4ad9-823a-481a0f2aad9b","resolution":{"observed_at":"2026-08-07T13:51:38.891782Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:37.462474Z","title":"Characterization of tor traffic using time based features,","venue":null,"work_id":"0bb1e525-af8e-4264-a6c5-78c414d7c5ee","year":2017},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.035006Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:277a4f65efbfc7719c3db430900e878f36888095ba4ad57e6ad4d5c59c077d8f","observation_id":"fe890e24-86b9-4db9-abc9-6b6c9b17746d","resolution":{"observed_at":"2026-08-07T13:51:37.510230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:37.971683Z","title":"Towards effective feature selection in machine learning-based botnet detection approaches,","venue":null,"work_id":"496b30b5-522b-4e64-9d22-f04e7fb00aa1","year":2014},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:29.806447Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:a244100f2463660df55b9009186b861b2a95531636fd16e67328749b4bca3bc2","observation_id":"9c5f8090-b10f-4580-af88-e8df0318bf7b","resolution":{"observed_at":"2026-08-07T13:51:38.159432Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:37.118614Z","title":"& Xiong, G","venue":null,"work_id":"70250f79-da15-4d94-bbf6-30167eb51a0f","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.286392Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:a3173a5d85d568de1efdfaeebff1def6db8d11cecbc8f29c5c173dbed0ac17b3","observation_id":"8e237f06-db64-450c-bc40-c61f8519d894","resolution":{"observed_at":"2026-08-07T13:51:37.174607Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:36.947187Z","title":"Zero-relabelling mobile-app identification over drifted encrypted network traffic,","venue":null,"work_id":"1b4f9a6a-d01f-447d-828f-139f476e9080","year":2023},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.420159Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:428363eb8e2ba91eb53592b549a547583ffcbe8258796ccb421918d3c505aa72","observation_id":"7b364862-4971-4a80-9463-36312ffe4c4a","resolution":{"observed_at":"2026-08-07T13:51:37.012604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:37.265439Z","title":"Characterization of encrypted and VPN traffic using time- related features,","venue":null,"work_id":"085e07f8-8ae4-4e2d-b1f5-a3c20f750d15","year":2016},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.173458Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:604ea95c7e799989f6da1b99d7c5d7e787c20f7d3e67961ed1cdd2038cccfb28","observation_id":"b2b21b1a-ed90-4658-a463-c8749a1c7a0a","resolution":{"observed_at":"2026-08-07T13:51:37.356805Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:36.595804Z","title":"Towards non-i.i.d. image classification: A dataset and baselines,","venue":null,"work_id":"a8d7086e-e637-4fa3-b554-e9be89cfd74b","year":2021},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.660516Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:d8d75ab1a0d543c2086c8b0b9fa79c7de4caba8f7141e651ee528a16afd30c11","observation_id":"b3fa444f-24ef-4628-b420-6a2d8ed4bb89","resolution":{"observed_at":"2026-08-07T13:51:36.673862Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:36.438412Z","title":"Optimizing feature selection for efficient encrypted traffic classification: A systematic approach,","venue":null,"work_id":"e66933d1-3530-4e48-959f-8c6b0472809c","year":2020},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.775282Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:07f04800db8ef2ebd3fda19693301fdf13b528399f3fc942ed99a472c786883e","observation_id":"d198e8c7-561e-452a-83fd-38142e941198","resolution":{"observed_at":"2026-08-07T13:51:36.504997Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:36.757718Z","title":"Flowprint: Semi-supervised mobile-app fingerprinting on encrypted network traffic,","venue":null,"work_id":"3efce4ee-c857-4da4-8c16-6bce3aaa0a3e","year":2020},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.523202Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:d2ff8ecdfa4c68036b79ec5e2d3452e6e1b9cce38d56692c3d87f0e5ff348300","observation_id":"ba1161b0-1466-4b44-ac71-2dd2090eb4db","resolution":{"observed_at":"2026-08-07T13:51:36.854390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:36.211822Z","title":"& Greenstadt, R","venue":null,"work_id":"dbc6a1cb-d5ca-4d68-a3f9-72212513f384","year":2014},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.919657Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:e11ef991567711f0ec3e926a86b6bf18f6c420b054f54c59bf9f39dfb06f2b35","observation_id":"6143bea5-4d7e-4699-abe3-37812f9ac26f","resolution":{"observed_at":"2026-08-07T13:51:36.241448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:35.953652Z","title":"Adawfpa: Adaptive online website fingerprinting attack for tor anonymous network: A stream-wise paradigm,","venue":null,"work_id":"015f1a93-ac1b-4f99-813c-56eb32092665","year":2019},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.998983Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:d6117e5eec1b36fa868ce4cfae0fdb3c8c1e52cdaa1ed76103a4d65f72131043","observation_id":"2a9e1be5-ec7e-43d4-9ae7-a8dd24a00101","resolution":{"observed_at":"2026-08-07T13:51:36.110666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:36.285911Z","title":"Language models as knowledge bases?","venue":null,"work_id":"d5bcf90d-ee3c-4bb1-bd3f-cd70a4e06534","year":2019},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:30.849243Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:0ea99c402fc60728ecb7a391b2353cc7edc1dbf5a3e5e25554c47992f9d8fed6","observation_id":"6198a799-a00d-485f-b9aa-dc3534d93638","resolution":{"observed_at":"2026-08-07T13:51:36.323479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:35.296852Z","title":"Robust smartphone app identification via encrypted network traffic analysis,","venue":null,"work_id":"509b8038-ceab-4888-95f9-c2087687bfb1","year":2018},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:31.126296Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:84cd533d1b148cd14c7043e3abca5e58b12e7d4946cf27e7e7598d3114973522","observation_id":"14aa8842-ac4e-4815-b053-d25dc80ce332","resolution":{"observed_at":"2026-08-07T13:51:35.429503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:34.957018Z","title":"Accurate mobile-app fingerprinting using flow-level relationship with graph neural networks,","venue":null,"work_id":"d116bf44-cc37-4f84-83e9-262eed8a9299","year":2022},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:31.209454Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:f040922b5b0a3a08c0ed01f9c5dfe52ddd416d8747517bb125924f9b43c0799a","observation_id":"d88431a6-4f08-43f6-a51a-676a31809b1b","resolution":{"observed_at":"2026-08-07T13:51:35.119673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:35.627631Z","title":"Adaptive encrypted traffic fingerprinting with bi-directional dependence,","venue":null,"work_id":"5c0778ba-a0ae-4eab-b5a7-133c26eaca08","year":2016},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:31.054096Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:838517f6a2b33f9e26fff7508fce9145df1331a7233e8550121005b5860c2d9b","observation_id":"affe029c-71fa-47fe-9677-8684dab610b7","resolution":{"observed_at":"2026-08-07T13:51:35.779070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:34.388220Z","title":"Learning to prompt for vision-language models,","venue":null,"work_id":"9639c5b8-4c90-483b-9d97-6fbca8c6b271","year":2022},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:31.394711Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:d7816e325f5bd4145431f3e9f3fd269883e1d676cf2c86add14fb132ca0f0601","observation_id":"d9c896eb-80cb-4cad-bf5d-304871683546","resolution":{"observed_at":"2026-08-07T13:51:34.509508Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:34.136426Z","title":"Transfg: A transformer architecture for fine-grained recognition,","venue":null,"work_id":"64c5fbb8-a973-43d5-a4c1-f4a8725103da","year":2022},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:31.480548Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:4b8fa81d9322f48dcb95aa6047a998a10f993d74239bccad84adb87d45a9fd2e","observation_id":"79057dd6-a1b4-49bc-aabb-ab57b030dc60","resolution":{"observed_at":"2026-08-07T13:51:34.240692Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:34.694722Z","title":"& Xiong, G","venue":null,"work_id":"ea566575-5c8c-40d5-9ae6-8facd455f4a9","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:31.316154Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:0d7f684d3758825777250d852ae37011a803700716f12e18b7f342e928d01db1","observation_id":"a50110bc-9586-4f3f-a94b-de45643317f1","resolution":{"observed_at":"2026-08-07T13:51:34.815837Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:33.622629Z","title":"Mt-flowformer: A semi-supervised flow transformer for encrypted traffic classification,","venue":null,"work_id":"797f5d2e-a6ac-4867-9c2a-6545fc37f092","year":2022},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:31.712140Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:6d68a3e2fc3848eb4c6ff81df9f1bf57c83b6f0abb29612cf101f047f13ac332","observation_id":"f9b9aa7d-bc17-4c26-a991-538223ba18cf","resolution":{"observed_at":"2026-08-07T13:51:33.731037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:33.339298Z","title":"& Xie, Y","venue":null,"work_id":"74329662-5922-4ae0-a25a-bd11e610899e","year":2023},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:31.852004Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:7d959c40c7d5339ff0fd081e36664f979f8f1f0bc362a57b888a73c70406e80c","observation_id":"f336a8cf-7196-4351-a810-ba952e77a716","resolution":{"observed_at":"2026-08-07T13:51:33.444441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:33.856145Z","title":"How can we know what language models know,","venue":null,"work_id":"fbc2a646-fcf5-4567-8ba2-ba508547f1cd","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:31.573690Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:00204826bd8edaa9433a9768b596f1e9f75b9b0d1b45ce623fb00e88f4c171d5","observation_id":"5f2a3d3b-63f5-4419-88bf-2d1afdc5a012","resolution":{"observed_at":"2026-08-07T13:51:33.973659Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:32.835361Z","title":"& Han, J","venue":null,"work_id":"01ed2304-0e00-4ac9-a2db-90b09eb096fd","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:32.180686Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:045a3cbbdf8e09ab6586959bb652c097cb5bc58ea519168168136c7e00d32467","observation_id":"a5e6cb17-f4cc-49c4-99a7-3bfc97734444","resolution":{"observed_at":"2026-08-07T13:51:32.951385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:32.540254Z","title":"& Liu, Y","venue":null,"work_id":"af5e52ed-8577-496a-8cea-fd158bc5642b","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:32.338793Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:dc549a5ee6a3fb8a9502a4ec947de738f74bc169a178726ba40e8974e96c5d48","observation_id":"b2583eb3-7f41-4f2c-86e6-c8a7172bac07","resolution":{"observed_at":"2026-08-07T13:51:32.699156Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:33.100611Z","title":"& Hajishirzi, H","venue":null,"work_id":"d05dd78e-0af7-4382-bea8-b366071f1263","year":2023},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:32.001261Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:86081ee933b4604ae84780e0b8879fd232c2a604db5cf1b0b50bb2670d3b58fa","observation_id":"f6f27b16-bbf8-4d02-9a25-ccf671442454","resolution":{"observed_at":"2026-08-07T13:51:33.226833Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:37.614660Z","title":null,"venue":null,"work_id":"a9256d9c-55ba-4dc6-ad1f-c45507e2e851","year":2014},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:29.937734Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:f7dc8666ed1283eb4fc80347f0567c194549e49d7960298586d9b5755194325d","observation_id":"1a7cc038-09ab-4a4a-8c12-5a73efaadfbb","resolution":{"observed_at":"2026-08-07T13:51:37.760879Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:51:40.669745Z","title":"7156-7173 (2024)","venue":null,"work_id":"8c7945bb-517e-4b23-b8f1-09411674e1e3","year":2024},"citing_paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:28.403610Z"},"links":{"citing_paper":"/paper/2505.20866"},"observation_digest":"sha256:08c8da5b7db37bb5458d818235567b5f343e414691bacb36a60d4b3ec67e4af5","observation_id":"a045c14e-c49f-49e2-8a40-4a1f36c17fee","resolution":{"observed_at":"2026-08-07T13:51:40.794287Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.20866","last_updated":"2025-05-27T08:18:16Z","latest_version":1,"primary_category":"cs.CR","snapshot_observed_at":"2026-08-14T22:44:49.770845Z","submitted_at":"2025-05-27T08:18:16Z","title":"Respond to Change with Constancy: Instruction-tuning with LLM for Non-I.I.D. Network Traffic Classification"},"reference_resolution":{"displayed":52,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":3,"unresolved":4,"verified_exact":0,"verified_fuzzy":45},"total_outbound_references":52},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2505.20866."}