{"as_of":"2026-08-09T05:44:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d988f8a5dd5fbbf61a5a1229f62bf2640dbf49eba35485f0614d35cfcbca9493","coverage":[{"denominator":9,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T06:02:46.494113Z","state":"measured"},{"denominator":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2502.08213/citation-record","integrity":"/paper/2502.08213/integrity","json":"/paper/2502.08213/citation-record.json","paper":"/paper/2502.08213"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T06:02:46.642923Z","title":"N., Kaiser, Ł, & Polosukhin, I","venue":null,"work_id":"054162e8-f983-4d13-ac8a-8a40945fd85c","year":2017},"citing_paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T06:02:46.456932Z"},"links":{"citing_paper":"/paper/2502.08213"},"observation_digest":"sha256:9c7032222ec8044e66fdb8c5b07b24f2e85873a15f5d54edcf35405e632d4f2a","observation_id":"6c8c7359-f0d5-4f31-bf96-ecafa745ed92","resolution":{"observed_at":"2026-08-08T06:02:46.647378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-08T06:02:46.627540Z","title":", Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., & others","venue":null,"work_id":"083053fb-3347-46e3-8fdf-ec8aab24ae31","year":2020},"citing_paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-08T06:02:46.461784Z"},"links":{"citing_paper":"/paper/2502.08213"},"observation_digest":"sha256:dcb747ccdcf1f5c1d1fa2e5792a851885d215c02865ae51b722551122d8aca98","observation_id":"daeb55dc-a610-476e-8a36-0fbf41cf4b57","resolution":{"observed_at":"2026-08-08T06:02:46.632963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-08T06:02:46.466109Z","title":"B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dh ariwal, P.,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T06:02:46.466109Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2502.08213"},"observation_digest":"sha256:817d9693ae32a5f545ace6f09aacf9bae8b194bb8845ed15f8d63ece6b4686a4","observation_id":"605685a0-5a10-4ef9-8e92-0dfb62f9790d","resolution":{"observed_at":"2026-08-08T06:02:46.466109Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.01108","last_updated":"2020-03-01T02:57:50Z","snapshot_observed_at":"2026-08-07T19:07:36.327251Z","submitted_at":"2019-10-02T17:56:28Z","title":"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.01108","snapshot_observed_at":"2026-08-08T06:02:46.470988Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T06:02:46.470988Z"},"links":{"cited_paper":"/paper/1910.01108","citing_paper":"/paper/2502.08213"},"observation_digest":"sha256:d7c2d84036d8ed9d33be780b619e7225835c5c3509ff03f15013bb5a97f230e1","observation_id":"b0089b2c-7d1f-4f2b-8a33-0a0bdf34c9c2","resolution":{"observed_at":"2026-08-08T06:02:46.470988Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1909.10351","last_updated":"2020-10-16T02:12:46Z","snapshot_observed_at":"2026-08-07T22:21:53.513424Z","submitted_at":"2019-09-23T13:05:35Z","title":"TinyBERT: Distilling BERT for Natural Language Understanding","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.10351","snapshot_observed_at":"2026-08-08T06:02:46.475725Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T06:02:46.475725Z"},"links":{"cited_paper":"/paper/1909.10351","citing_paper":"/paper/2502.08213"},"observation_digest":"sha256:a8f9338ba7256ae70ddf3f4e8072694d27b4eb91245ef2f0fde27835e8a3133f","observation_id":"e7aa24e4-5d35-4d94-90f2-cb1c8ed7de4c","resolution":{"observed_at":"2026-08-08T06:02:46.475725Z","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":"2026-08-08T06:02:46.613084Z","title":null,"venue":null,"work_id":"2c6fb770-e60a-43e4-8784-594232e3e071","year":2019},"citing_paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T06:02:46.480648Z"},"links":{"citing_paper":"/paper/2502.08213"},"observation_digest":"sha256:812d872175a0b4222a483545e650ad295858fd078212f57aa2f0f000e495dc1c","observation_id":"f85970ad-1bcb-47ad-a017-f565b8efa81e","resolution":{"observed_at":"2026-08-08T06:02:46.617570Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-07T07:43:16.294957Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-08T06:02:46.485564Z","title":"J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wan g, L., & Chen, W","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T06:02:46.485564Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2502.08213"},"observation_digest":"sha256:19ebccb70ad725792514b44fbcaf37687eb04cf309f8a56ed0e159f36bf60685","observation_id":"9e6cab8f-3690-443b-8756-0cbb472f8eb0","resolution":{"observed_at":"2026-08-08T06:02:46.485564Z","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":"2026-08-08T06:02:46.598720Z","title":null,"venue":null,"work_id":"661fd5aa-46d2-46cc-923e-a05ffa40b0d4","year":2020},"citing_paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T06:02:46.490119Z"},"links":{"citing_paper":"/paper/2502.08213"},"observation_digest":"sha256:03d1c264b8330dd4f5b9f5d3e4212479220e7eb105d727b4484405ec7e7bbffb","observation_id":"b5772f17-f694-4c7c-8fcd-f2584634c58d","resolution":{"observed_at":"2026-08-08T06:02:46.603211Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-08T06:02:46.582100Z","title":null,"venue":null,"work_id":"f07b12b0-b475-4555-92eb-944b6b6a810d","year":2019},"citing_paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T06:02:46.494113Z"},"links":{"citing_paper":"/paper/2502.08213"},"observation_digest":"sha256:f438153789302acadada84cad29eea335057ec9abbf0f39ed0f6890e408d4fc5","observation_id":"49846c23-b16d-47c1-8882-7d1b388724af","resolution":{"observed_at":"2026-08-08T06:02:46.587350Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.08213","last_updated":"2025-02-12T08:48:55Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-08T05:57:18.082877Z","submitted_at":"2025-02-12T08:48:55Z","title":"LLM Modules: Knowledge Transfer from a Large to a Small Model using Enhanced Cross-Attention"},"reference_resolution":{"displayed":9,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":2},"total_outbound_references":9},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2502.08213."}