{"as_of":"2026-08-16T09:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:8472b4df27ee9fdc1ac149d29f11b0c45c2aee3aeff108f8bc257d28c4954b91","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T13:57:49.495034Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T10:59:35.866884Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T10:59:37.841504Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"cited_work":{"arxiv_id":"2412.12654","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.12654","snapshot_observed_at":"2026-08-06T10:59:37.841504Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","venue":"cs.CV","work_id":"594d0873-3ce0-4c94-8b45-9df966373799","year":2024},"citing_paper":{"arxiv_id":"2507.23237","last_updated":"2025-07-31T04:29:49Z","snapshot_observed_at":"2026-08-06T10:59:33.732725Z","submitted_at":"2025-07-31T04:29:49Z","title":"Ambiguity-Guided Learnable Distribution Calibration for Semi-Supervised Few-Shot Class-Incremental Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T10:59:35.866884Z"},"links":{"cited_paper":"/paper/2412.12654","citing_paper":"/paper/2507.23237"},"observation_digest":"sha256:3c5b2f76597eeb6519c7fda7d6399e5660fefa745024f3998a11259e5c4161af","observation_id":"88f11dc1-28e8-4cbf-9a22-5a7cd0694522","resolution":{"observed_at":"2026-08-06T10:59:37.916854Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.12654/citation-record","integrity":"/paper/2412.12654/integrity","json":"/paper/2412.12654/citation-record.json","paper":"/paper/2412.12654"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:57:50.607321Z","title":"Learning to learn task-adaptive hyperparameters for few-shot learning","venue":null,"work_id":"155f9259-aa3b-42cc-962c-87d0d79cfba2","year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.191434Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:8acbb5eb75e3f6ae756e99f56626fa2889aef84c405fdf9604588cb239d54541","observation_id":"153cef18-0938-4891-8328-52f0e741128c","resolution":{"observed_at":"2026-08-11T13:57:50.611712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.199156Z","title":"Dark experience for gen- eral continual learning: a strong, simple baseline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.199156Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:a883ef6cd3dd2ac0ccf4e985c93806e83368b6af1516d7655748aa246be45b87","observation_id":"2bcd2003-3a0a-4f70-a56e-a12f87d74988","resolution":{"observed_at":"2026-08-11T13:57:49.199156Z","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":"2026-08-11T13:57:50.585494Z","title":"Learning imbalanced datasets with label- distribution-aware margin loss","venue":null,"work_id":"bd05fad3-e907-4afa-bc4b-1b5ce950edd9","year":2019},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.203564Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:3a5033dba33a4898599ad825820d1cd3b5c41be043d4a993424b3e7ba8eb780b","observation_id":"28d0d063-d46d-4db2-bb56-5c055ac4598d","resolution":{"observed_at":"2026-08-11T13:57:50.590179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.209926Z","title":"Metafscil: A meta-learning approach for few-shot class incremental learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.209926Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:806de75857a60ec0690196a9dc4ca8115e5e9c2f2a1704e7c6ffd64ed6f8cdb7","observation_id":"bb3aae51-7b2c-4381-9e44-785dce785b60","resolution":{"observed_at":"2026-08-11T13:57:49.209926Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:57:49.215641Z","title":"Imagenet: A large-scale hierarchical image database","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.215641Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:457e3fb0ade07773363d777faa82a988656ed36b1426c59e6f7f4df0e2db65df","observation_id":"dab56299-d929-4970-b3c4-d740f5921bf3","resolution":{"observed_at":"2026-08-11T13:57:49.215641Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:57:49.225849Z","title":"Arcface: Additive angular margin loss for deep face recognition","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.225849Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:c24fadd950d1f7191255d31ba4e7f82aaddc93555c6e761ae7bcbb46991735f9","observation_id":"0781642d-4f01-4d82-8cc6-ba94d1c60233","resolution":{"observed_at":"2026-08-11T13:57:49.225849Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:57:49.230621Z","title":"Model- agnostic meta-learning for fast adaptation of deep networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.230621Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:3f142cf7b935dc434577392557c08f299d0b94df0cb803df0c4dafbacf9947ae","observation_id":"d26e836b-7b57-4328-a1ae-b0f7b348440f","resolution":{"observed_at":"2026-08-11T13:57:49.230621Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6211","last_updated":"2015-03-04T01:43:31Z","snapshot_observed_at":"2026-08-14T23:50:42.566579Z","submitted_at":"2013-12-21T06:31:41Z","title":"An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6211","snapshot_observed_at":"2026-08-11T13:57:49.235784Z","title":"An empirical investigation of catas- trophic forgetting in gradient-based neural networks","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.235784Z"},"links":{"cited_paper":"/paper/1312.6211","citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:de90a52427578cdd3fdd16ff86685953e4fe3b0959068f4421507cef6d08921d","observation_id":"916080cb-2e78-4f22-b8e6-4a5c6b214e3c","resolution":{"observed_at":"2026-08-11T13:57:49.235784Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00752","last_updated":"2024-05-31T17:55:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-01T18:01:34Z","title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00752","snapshot_observed_at":"2026-08-11T13:57:49.241609Z","title":"Mamba: Linear-time sequence modeling with selective state spaces","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.241609Z"},"links":{"cited_paper":"/paper/2312.00752","citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:33316928427e2c8b18905c40680289dbec521fcc7c8e8c326b90b7be6ebe4a67","observation_id":"aaa2f20f-c65d-4754-bb06-d6a4bc7ff0e8","resolution":{"observed_at":"2026-08-11T13:57:49.241609Z","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":"2026-08-11T13:57:50.397342Z","title":"Adaptive distribution calibration for few- shot learning with hierarchical optimal transport","venue":null,"work_id":"a6403a3c-79c5-4f2a-a93f-5c6876c4ad85","year":null},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.249617Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:a84f3aa23356dcd9b1b8dd3bdb9759f33d2ef402a5b7793c08a6eb335c5fbb8d","observation_id":"dd9b9d9d-1b99-40f6-b396-393cef62817c","resolution":{"observed_at":"2026-08-11T13:57:50.402944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.255346Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.255346Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:839950c64b77761967ba934976cfe179c53eedc82aad5e1f3ef80704adf34c1b","observation_id":"69550af6-a585-404f-861c-84f34ae4767d","resolution":{"observed_at":"2026-08-11T13:57:49.255346Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:57:49.262477Z","title":"Mask r-cnn","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.262477Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:42c83b2554650a23e9d7d9525f0555e4b6b77542f9d2927f2e29c2b4934e3682","observation_id":"be1da73f-5b0e-4042-be88-8f82ab88bc2e","resolution":{"observed_at":"2026-08-11T13:57:49.262477Z","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":"2026-08-11T13:57:50.357585Z","title":"A theoretical study on solving continual learn- ing","venue":null,"work_id":"03e9912a-124b-4575-8bd8-2c3276509de9","year":2022},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.268108Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:b22f8690a6024aa04bbd566b028658857db00edc311e48a15a35321139e7dc1f","observation_id":"7c8aa1db-af80-4374-b2f6-cd6edbde3f4c","resolution":{"observed_at":"2026-08-11T13:57:50.363076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.274227Z","title":"Learning multiple layers of features from tiny images","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.274227Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:5a494109749833ba4177f7d7dbc6e0a7d204c0b14311f761134d3b159b75fec5","observation_id":"02fe2711-16c6-4294-aa45-45693d1be64a","resolution":{"observed_at":"2026-08-11T13:57:49.274227Z","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":"2026-08-11T13:57:50.320583Z","title":"Unsupervised model personalization while preserving privacy and scalabil- ity: An open problem","venue":null,"work_id":"5947b881-3022-41ce-b1aa-bd21bb254fde","year":2020},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.283306Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:03c2f6417c29a23b2a27df41778aec17a1c5afb3f7206f55af2532cc8bc0441f","observation_id":"602634ee-fadd-4a3d-aeb4-e8e038d2f20a","resolution":{"observed_at":"2026-08-11T13:57:50.326381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:50.297723Z","title":"Adversarial feature hallucination networks for few-shot learning","venue":null,"work_id":"b916a314-6038-4d94-bc07-82c7ed220fb4","year":2020},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.289950Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:4d597d5c9250a58c906dec9a4e315ea1c7bd507e966a0a780668a4675de5ad18","observation_id":"446ab9c8-f8fb-4633-98a8-ef16c4518583","resolution":{"observed_at":"2026-08-11T13:57:50.303788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:50.274959Z","title":"Adjusting logit in gaussian form for long-tailed visual recognition","venue":null,"work_id":"c7257faf-7a21-40ff-bf0c-9e2a4733f85f","year":2024},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.294610Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:1310ffbf04ad1b2865dab8a1160a9df747deec3537b5a8780b4660b8f34e431e","observation_id":"7bc754d1-0cf0-4640-90a6-0c86d0034238","resolution":{"observed_at":"2026-08-11T13:57:50.280799Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:50.259015Z","title":"Feature space transfer for data augmen- tation","venue":null,"work_id":"448e5c2a-44f1-4de5-9564-8102cb9af510","year":2018},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.299151Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:591636c119090a36adb05ba81616383e70b6fff24fef3f3aa03680bf1ac813fe","observation_id":"6e6078cf-dcea-4be3-8b9f-3d3a7adc3bfb","resolution":{"observed_at":"2026-08-11T13:57:50.264272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.302796Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.302796Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:5669d5c7511ac53c4f398f7f922554057e397eb58265f865981ff1f602c859db","observation_id":"c20cfbf5-d473-426e-ab2f-01fe25c7e292","resolution":{"observed_at":"2026-08-11T13:57:49.302796Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1703.08033","last_updated":"2017-03-23T12:19:09Z","snapshot_observed_at":"2026-08-14T21:10:22.627004Z","submitted_at":"2017-03-23T12:19:09Z","title":"Generative Adversarial Residual Pairwise Networks for One Shot Learning","version":1},"cited_work":{"arxiv_id":"1703.08033","doi":null,"metadata_source":"pith","pith_arxiv_id":"1703.08033","snapshot_observed_at":"2026-08-11T13:57:49.615466Z","title":"Generative Adversarial Residual Pairwise Networks for One Shot Learning","venue":"cs.CV","work_id":"7c82cb57-afa9-4350-908f-e39ee3495d80","year":2017},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.307084Z"},"links":{"cited_paper":"/paper/1703.08033","citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:02d8ad86aa2d420488667243348e30a8c16e7c60c3bd7424910d2d759215f0a0","observation_id":"25844376-258e-4103-975b-7ae67d85883b","resolution":{"observed_at":"2026-08-11T13:57:49.625787Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2007.07314","last_updated":"2021-07-09T21:23:25Z","snapshot_observed_at":"2026-08-08T11:03:52.719052Z","submitted_at":"2020-07-14T19:27:13Z","title":"Long-tail learning via logit adjustment","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.07314","snapshot_observed_at":"2026-08-11T13:57:49.311819Z","title":"Long-tail learning via logit adjustment","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.311819Z"},"links":{"cited_paper":"/paper/2007.07314","citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:38a5168a7ed1c8e42403d26748cdb7e23587bdc699e2454a24dede6490e20adc","observation_id":"4ba92004-6628-4f40-b196-e49f83adc5db","resolution":{"observed_at":"2026-08-11T13:57:49.311819Z","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":"2026-08-11T13:57:50.231509Z","title":"Few-shot class-incremental learning from an open- set perspective","venue":null,"work_id":"9e8d1307-fe8b-40e1-9f2b-e51a5f0c2548","year":2022},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.328764Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:c29c10602a983df5d07b940ef38d4cad2753067f1779cab9b2fcf59ac95eb1c9","observation_id":"e13f878d-d6f2-4fc1-a3ee-41f4cac4d407","resolution":{"observed_at":"2026-08-11T13:57:50.235984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:50.211741Z","title":"icarl: Incremental classifier and representation learning","venue":null,"work_id":"2cf93fcf-78b3-4c0e-b044-b5f077879cd3","year":2001},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.333126Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:a9b19a8e22002745b0fd562b6ef892b8f0336760a147a66cbdc08deb34060612","observation_id":"d2174a86-11db-4d37-a318-b71210bbc1a7","resolution":{"observed_at":"2026-08-11T13:57:50.219867Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.337338Z","title":"Imagenet large scale visual recognition challenge","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.337338Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:108b8feab26f5d449f95b169584e758aab3267417a5747372985658faf77e7ad","observation_id":"806af72d-5f1f-4f32-a99a-1e623416149c","resolution":{"observed_at":"2026-08-11T13:57:49.337338Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:57:49.341662Z","title":"Prototypical networks for few-shot learning","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.341662Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:91b18c1f41eb7f4b06f5c4338231620f41237a2630a4f9949edf13779b45bdfe","observation_id":"f58acbf5-871a-4f5f-b4d8-7bff9c24526d","resolution":{"observed_at":"2026-08-11T13:57:49.341662Z","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":"2026-08-11T13:57:50.166671Z","title":"Learning with fantasy: Semantic-aware virtual contrastive constraint for few-shot class-incremental learning","venue":null,"work_id":"a09143fd-c03b-4c53-8fa4-64e9386c42b9","year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.346060Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:43c81ea9b79bcfb864e11cee3154905f282dcc00df31a914a0186f24c0425aed","observation_id":"d62b8f50-eb71-4324-888d-1557fe873f4b","resolution":{"observed_at":"2026-08-11T13:57:50.172291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:50.144895Z","title":"Pseudo re- hearsal using non photo-realistic images","venue":null,"work_id":"479dfdba-8992-4e3b-a3c4-e60035b0f7c3","year":2020},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.352912Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:3060a46aaa9d371a1a997753a29ee3177af07bb43681ef208525c2396a952c4e","observation_id":"cdf9548b-e74f-4b37-b9ad-95759fa16e44","resolution":{"observed_at":"2026-08-11T13:57:50.152580Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:50.119132Z","title":"Few-shot class- incremental learning","venue":null,"work_id":"9d2bd4e4-7406-42f4-adde-866b7778ff94","year":2020},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.357657Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:7bcc7efcaaa359915de5cae9e05a3b079303f0b1fbc22fea6ea0f21b175f1e1a","observation_id":"d7599773-70a4-475c-ac52-b43fb02f78bd","resolution":{"observed_at":"2026-08-11T13:57:50.123868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:50.100596Z","title":"Local and global logit adjustments for long-tailed learning","venue":null,"work_id":"72e4d0c3-4438-4119-b728-373563ceb47b","year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.362075Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:e88a6e93232ee28c0c38eaad0a2433f6a6a72a2e2512fc7d460ef18e672a1d0c","observation_id":"3c5539b7-da29-4347-9125-bad163877205","resolution":{"observed_at":"2026-08-11T13:57:50.106264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.369936Z","title":"Visualizing data using t-sne","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.369936Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:7fc4f348ddfe80e3cb7cac5a0fb01c973c76e5e6a4671143184bd21da8b8f36f","observation_id":"e96167a1-beca-4651-b547-61759238b0e2","resolution":{"observed_at":"2026-08-11T13:57:49.369936Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:57:49.374423Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.374423Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:88064a2551ed3135f0b6c28cf2fb017de1765a21a99280f5773b46afd40b1792","observation_id":"85c32cef-0b21-4108-a61e-cbb4f7da6e56","resolution":{"observed_at":"2026-08-11T13:57:49.374423Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T13:57:49.385138Z","title":"The caltech-ucsd birds-200-2011 dataset","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.385138Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:dcca952c699aa66bd416c228959feced13896ee93d71e318e79dd141384364e7","observation_id":"39d004b9-4a0b-405f-ab40-77dbc9b94d00","resolution":{"observed_at":"2026-08-11T13:57:49.385138Z","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":"2026-08-11T13:57:50.024778Z","title":"Cosface: Large margin cosine loss for deep face recognition","venue":null,"work_id":"40ce55d2-01af-4e43-9706-c1a637d96fa8","year":2018},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.391073Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:5fdc7e2eba42b842d39e032e115e1f49d628bfaab6880e9d37df599fa8bf8fd1","observation_id":"f3f97cb0-104e-409c-b6d1-50062f3a9dd5","resolution":{"observed_at":"2026-08-11T13:57:50.029435Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:50.005120Z","title":"Few-shot class-incremental learning via training-free prototype calibration","venue":null,"work_id":"69fd4768-bc55-4f93-b9a6-95b834093cb3","year":2024},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.399903Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:cdce1acdc9745516387ad1f2125558244d16e1097369ba102cb4a78652ad9896","observation_id":"11fcde3e-ce90-4cc4-87be-964fe79461f1","resolution":{"observed_at":"2026-08-11T13:57:50.012185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.981655Z","title":"Margin calibration for long-tailed visual recognition","venue":null,"work_id":"237ab93f-7f62-45da-9772-869c5abec7d0","year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.410876Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:3cd776e0024021f1b4c296ea7da06b84f06f58a1fbb839227a73217362d28ef7","observation_id":"babeb446-80bf-4ce7-a744-41edfb9a5b40","resolution":{"observed_at":"2026-08-11T13:57:49.989059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.963333Z","title":"A unified generaliza- tion analysis of re-weighting and logit-adjustment for imbal- anced learning","venue":null,"work_id":"47487082-8fed-4a98-b3e1-cefbd98ddcdf","year":2024},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.415856Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:0cdea693648d6eb3bb4004ac0d79ed3c01a4fa290022a1e4f8115a3a751f74cf","observation_id":"7aa58a15-42ea-4fd9-bb4f-5d1bb1fb481a","resolution":{"observed_at":"2026-08-11T13:57:49.968420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.943623Z","title":"Learning imbalanced data with vision transformers","venue":null,"work_id":"b7181204-521c-49a9-bc92-989b7bf87577","year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.422194Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:4779232b8c625fe6d9a2747179f531ef770b719b648c5fbda98ef1c0d4f47034","observation_id":"067e5b0c-7a26-4813-81f9-afea5746ca1c","resolution":{"observed_at":"2026-08-11T13:57:49.949652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.924987Z","title":"Scrollnet: Dy- namicweight importance for continual learning","venue":null,"work_id":"83118df7-e97e-495a-89de-a3b5c42ed943","year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.428307Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:3907c0a4cfa955495c0083eb9dadd80b0b7f41c10c49f4436bdfe64c41d65c9b","observation_id":"f0d13714-a6e0-4d30-a6c5-63fb6655cff0","resolution":{"observed_at":"2026-08-11T13:57:49.931066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.06395","last_updated":"2021-08-15T04:44:18Z","snapshot_observed_at":"2026-08-13T20:29:49.315637Z","submitted_at":"2021-01-16T07:58:40Z","title":"Free Lunch for Few-shot Learning: Distribution Calibration","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.06395","snapshot_observed_at":"2026-08-11T13:57:49.432779Z","title":"Free lunch for few- shot learning: Distribution calibration","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.432779Z"},"links":{"cited_paper":"/paper/2101.06395","citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:0221ac66e71a1b7643546352814019bb47e90f4456c660b4bbd0cc54947b7fd5","observation_id":"35754ff6-6e73-49d0-bf4a-947bb5985cf0","resolution":{"observed_at":"2026-08-11T13:57:49.432779Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.03004","last_updated":"2023-02-06T18:39:40Z","snapshot_observed_at":"2026-08-13T12:49:58.443819Z","submitted_at":"2023-02-06T18:39:40Z","title":"Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class Incremental Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.03004","snapshot_observed_at":"2026-08-11T13:57:49.437796Z","title":"Neural collapse inspired feature- classifier alignment for few-shot class incremental learning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.437796Z"},"links":{"cited_paper":"/paper/2302.03004","citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:6b25b157165bb99d72cc9cda9c54ec07ca0b6c770e6d7acc65af02334ae58bcc","observation_id":"1a53c841-0d73-4ac4-989e-1c742c1b819f","resolution":{"observed_at":"2026-08-11T13:57:49.437796Z","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":"2026-08-11T13:57:49.895058Z","title":"Few-shot incremental learning with contin- ually evolved classifiers","venue":null,"work_id":"13cd9953-ce36-4398-97c8-29be16e7839f","year":2021},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.444112Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:e357c3861cc771e5ea2645da229dc8754a59493258c403bd8a901df891f5e83a","observation_id":"483f921c-4e27-417b-942e-6b39270805ca","resolution":{"observed_at":"2026-08-11T13:57:49.908337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.862437Z","title":"mixup: Beyond empirical risk minimiza- tion","venue":null,"work_id":"7e2f5d04-dbb4-4e81-84f8-3026d145cf0d","year":2017},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.448919Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:0f027969723185801692780cbfd9602d8fe256dea7f2b6d3342f9eea9d19c052","observation_id":"085a4d34-2d5a-4c2e-aaee-0e06cfce1109","resolution":{"observed_at":"2026-08-11T13:57:49.874340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.841931Z","title":"Class-incremental learning via deep model consolidation","venue":null,"work_id":"5fcbf93f-3a84-4bf4-88ff-41b5637bb869","year":2020},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.452695Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:78b20bd8812ae536c1e26fc21e9b67d231e80f688e5662955118efe0043ec9e6","observation_id":"952339d8-874d-459f-9821-efd1bd4ed790","resolution":{"observed_at":"2026-08-11T13:57:49.849567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.814521Z","title":"Few-shot class- incremental learning via class-aware bilateral distillation","venue":null,"work_id":"07301299-04bb-4336-bb43-927a3ed5de61","year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.462997Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:f94ae7d55c2f4908c1515ecaf9d471cf22fd18ad5276ce8c21cddebe0fc57493","observation_id":"52b5a7c6-c47f-4128-b5d7-59c129903991","resolution":{"observed_at":"2026-08-11T13:57:49.820496Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.781281Z","title":"Forward compatible few-shot class-incremental learning","venue":null,"work_id":"2be84172-b849-42d9-9557-4f32c6885df0","year":2022},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.468690Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:ee880679af297b8839c9204b0cce6af8d9a28d9808d0138ae7fbebf014640927","observation_id":"ad07c8b5-31cc-485f-8286-c80d33cb7fb4","resolution":{"observed_at":"2026-08-11T13:57:49.791236Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.752012Z","title":"Few-shot class-incremental learn- ing by sampling multi-phase tasks","venue":null,"work_id":"d6ada505-3738-459b-8e55-6ea3f7216e89","year":2022},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.474421Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:ba479a8db50335a6776ed7c0dee276e1f8a68743857a6ab078e0055f8ce10bab","observation_id":"58dbc578-7ec1-4fd0-85c8-0cb7b2b40252","resolution":{"observed_at":"2026-08-11T13:57:49.759027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.726053Z","title":"Self-promoted prototype refinement for few-shot class- incremental learning","venue":null,"work_id":"9a15ae2e-4bf5-4511-91f2-ff123df1fa4a","year":2021},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.478646Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:05b37ec7785c004710ef196cfcddecd94fb0dda576fecb795e92eb831652de5c","observation_id":"68bca43c-23e7-42a6-8c95-7a3c0b2c4adc","resolution":{"observed_at":"2026-08-11T13:57:49.732815Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-11T13:57:49.698975Z","title":"Gkeal: Gaussian kernel embedded analytic learning for few-shot class incremental task","venue":null,"work_id":"ef7b7ec9-4990-4e12-aee2-423235fbf975","year":2023},"citing_paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-11T13:57:49.495034Z"},"links":{"citing_paper":"/paper/2412.12654"},"observation_digest":"sha256:2e2c7f21745bc9a968282dc8a5130e0a837cd90601ccc5508ea12e1a4d61fc26","observation_id":"7c3866ea-5869-48fb-aa48-53eb7f1f66a9","resolution":{"observed_at":"2026-08-11T13:57:49.705023Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.12654","last_updated":"2024-12-17T08:21:46Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-11T13:49:31.841600Z","submitted_at":"2024-12-17T08:21:46Z","title":"CALA: A Class-Aware Logit Adapter for Few-Shot Class-Incremental Learning"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":19,"verified_exact":1,"verified_fuzzy":28},"total_outbound_references":48},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2412.12654."}