{"as_of":"2026-08-08T02:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7aa585676e524e615381ecc2d24cda7cba290277cde15c6d3753c3ce10e58f93","coverage":[{"denominator":59,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":59,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:45:24.415140Z","state":"measured"},{"denominator":59,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":59,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2505.23933/citation-record","integrity":"/paper/2505.23933/integrity","json":"/paper/2505.23933/citation-record.json","paper":"/paper/2505.23933"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T12:45:27.907679Z","title":"Building safe artificial intelligence: specification, robustness, and assurance, 2018","venue":null,"work_id":"a0a3b6f0-accb-40aa-a934-2fbc27108f22","year":2018},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:19.472616Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:b88c4c656cc198b4972fa6eb60383e4eb0c22e321e9a18f09e422eff48633d5e","observation_id":"18edf684-507e-4e8e-806e-4b050dc1ffaf","resolution":{"observed_at":"2026-08-07T12:45:27.990623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.19852","last_updated":"2025-04-04T11:14:49Z","snapshot_observed_at":"2026-08-05T20:02:35.087707Z","submitted_at":"2023-10-30T15:52:15Z","title":"AI Alignment: A Comprehensive Survey","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.19852","snapshot_observed_at":"2026-08-07T12:45:19.569160Z","title":"Ai alignment: A comprehensive survey.arXiv preprint arXiv:2310.19852, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:19.569160Z"},"links":{"cited_paper":"/paper/2310.19852","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:ee56bb7c77a1bd363e248dd1c7f2b6485378d0d603dbdedd0e98ee048125144c","observation_id":"a959ad30-9288-4a27-b0eb-f048203ecc84","resolution":{"observed_at":"2026-08-07T12:45:19.569160Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.06083","last_updated":"2019-09-04T18:53:10Z","snapshot_observed_at":"2026-08-07T14:27:46.872660Z","submitted_at":"2017-06-19T17:53:11Z","title":"Towards Deep Learning Models Resistant to Adversarial Attacks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.06083","snapshot_observed_at":"2026-08-07T12:45:19.686442Z","title":"Towards deep learning models resistant to adversarial attacks.arXiv preprint arXiv:1706.06083, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:19.686442Z"},"links":{"cited_paper":"/paper/1706.06083","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:089858782e95ed2f6019166b78e51e857ba4b2458ce63ea49bf1c6e08c51fd8a","observation_id":"8e03f6d7-cc57-4b03-a93d-9e19b6f254ac","resolution":{"observed_at":"2026-08-07T12:45:19.686442Z","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":"2026-08-07T12:45:19.776365Z","title":"Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:19.776365Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:08f60e2ed855815131bd3d4a3f6f17edff886c122a072a005791845720f771b7","observation_id":"b7388c36-c3c9-4d09-8cc6-467f53bfb322","resolution":{"observed_at":"2026-08-07T12:45:19.776365Z","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":"2026-08-07T12:45:19.863854Z","title":"Direct preference optimization: Your language model is secretly a reward model.Advances in Neural Information Processing Systems, 36:53728–53741, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:19.863854Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:b073e389182066567ff51bfbfa521c8cfe54ad37dd1edadb1eac23bede416363","observation_id":"b7d6c4b7-2ade-4c89-b881-af24a516686a","resolution":{"observed_at":"2026-08-07T12:45:19.863854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.08232","last_updated":"2020-02-21T15:51:23Z","snapshot_observed_at":"2026-07-06T07:54:16.157581Z","submitted_at":"2019-05-20T17:57:57Z","title":"Adversarially robust transfer learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.08232","snapshot_observed_at":"2026-08-07T12:45:20.032419Z","title":"Adversarially robust transfer learning.arXiv preprint arXiv:1905.08232, 2019","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:20.032419Z"},"links":{"cited_paper":"/paper/1905.08232","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:c7d7c4dd76e8a734a95cc2baa135130f5c7d7573740679c0cd987bfe32797fbd","observation_id":"978e0c25-c130-43f5-bd51-189558b54d1d","resolution":{"observed_at":"2026-08-07T12:45:20.032419Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03693","last_updated":"2023-10-05T17:12:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-05T17:12:17Z","title":"Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.03693","snapshot_observed_at":"2026-08-07T12:45:20.213466Z","title":"Fine- tuning aligned language models compromises safety, even when users do not intend to!arXiv preprint arXiv:2310.03693, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:20.213466Z"},"links":{"cited_paper":"/paper/2310.03693","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:80a959c7aa28e5664f9ae99bd9f98d0050b60bd09b8a3c123b17f21f6fdc3c57","observation_id":"740caea4-b6e2-4ce7-88f5-23f91cd2f966","resolution":{"observed_at":"2026-08-07T12:45:20.213466Z","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":"2026-08-07T12:45:27.726311Z","title":"Navigating the safety landscape: Measuring risks in finetuning large language models.Advances in Neural Information Processing Systems, 37:95692– 95715, 2024","venue":null,"work_id":"6a353ba7-eefa-4a45-90a9-4057efd58078","year":2024},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:20.382203Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:04ec917978bcbed7af7619dd4051c366be6e4b8fa90dfb69f8ab4b27aa4949b7","observation_id":"5d81f10b-c47f-4555-b80f-1dcdd7ee585d","resolution":{"observed_at":"2026-08-07T12:45:27.813472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.09390","last_updated":"2023-12-14T23:07:33Z","snapshot_observed_at":"2026-07-06T17:02:09.539730Z","submitted_at":"2023-12-14T23:07:33Z","title":"Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.09390","snapshot_observed_at":"2026-08-07T12:45:20.477961Z","title":"Weak-to-strong generalization: Eliciting strong capabilities with weak supervision.arXiv preprint arXiv:2312.09390, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:20.477961Z"},"links":{"cited_paper":"/paper/2312.09390","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:631143b36275f523ce50b1bb9d21fdd91a135d4eb8430105527c8d23adb29135","observation_id":"98ae2d19-a9c1-4632-906e-2a27f9b6bee6","resolution":{"observed_at":"2026-08-07T12:45:20.477961Z","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":"2026-08-07T12:45:20.591470Z","title":"Weak to strong generalization for large language models with multi-capabilities","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:20.591470Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:18cbb0e47ccbbb8f363c9d2954357478bc8f0f31d63b12b2608c7fe9a210cfc9","observation_id":"a8f047ed-363d-4e52-886e-c27ba2b8811d","resolution":{"observed_at":"2026-08-07T12:45:20.591470Z","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":"2026-08-07T12:45:27.560376Z","title":"On transfer of adversarial robustness from pretraining to downstream tasks.Advances in neural information processing systems, 36:59206– 59226, 2023","venue":null,"work_id":"4bcab83b-ac7f-4477-9266-25c614ec47b9","year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:20.677216Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:6c7e4fd2d855501c72b162755c53a410b0aecfbc3d41b13da49f79288b541646","observation_id":"d612b596-d958-4414-8ca4-13c2cd55bb52","resolution":{"observed_at":"2026-08-07T12:45:27.628597Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:27.426419Z","title":"When does contrastive learning preserve adversarial robustness from pretraining to finetuning?Advances in neural information processing systems, 34:21480–21492, 2021","venue":null,"work_id":"e29057a8-5648-41c1-a252-d14eccd73165","year":2021},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:20.773985Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:1e5b8b6904499ce71572a19ba2ba943e39016a60f25a94c67f17227f5e7d1672","observation_id":"60273b5c-c9e0-4a72-9715-5785906955f6","resolution":{"observed_at":"2026-08-07T12:45:27.483299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:27.342860Z","title":"Neural population geometry: An approach for understanding biological and artificial neural networks.Current opinion in neurobiology, 70:137–144, 2021","venue":null,"work_id":"721540c3-ab96-4988-afcd-fc0e50b6a044","year":2021},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:20.998214Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:5c0a37b80aa953071f9a4a3358730eb0e8453fab40910ccb5a7bcc5fd5337b2a","observation_id":"624563bd-36ca-449c-900c-d683dfcc5e06","resolution":{"observed_at":"2026-08-07T12:45:27.381524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:21.224236Z","title":"Catalyzing next-generation artificial intelligence through neuroai.Nature communications, 14(1):1597, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.224236Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:0e1c697ef8816b2947054a2c58eeebb8ed9f29195c493853105a5f6db7b708a7","observation_id":"966b3927-5e68-41af-bcfc-ed9fb7b5c404","resolution":{"observed_at":"2026-08-07T12:45:21.224236Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.18526","last_updated":"2025-04-03T02:40:12Z","snapshot_observed_at":"2026-08-04T19:41:48.321579Z","submitted_at":"2024-11-27T17:18:51Z","title":"NeuroAI for AI Safety","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.18526","snapshot_observed_at":"2026-08-07T12:45:21.293202Z","title":"Neuroai for ai safety.arXiv preprint arXiv:2411.18526, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.293202Z"},"links":{"cited_paper":"/paper/2411.18526","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:d1d0f2706428ae0b50ae98ae77ca75720cde1d82ec4c0de3250e67c5a12f1dbb","observation_id":"3d6c40a3-63f3-428a-b2ff-b199a4def170","resolution":{"observed_at":"2026-08-07T12:45:21.293202Z","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":"2026-08-07T12:45:27.225312Z","title":null,"venue":null,"work_id":"be0aa691-3448-4b17-8e80-beb7b5edc887","year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.376183Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:65a8a0fb79ddc660167d289ec454ec9896d46f47ccf78e565d5aec23ba294fe8","observation_id":"410a28ab-6c5d-44f1-bbee-7bfba6155ac4","resolution":{"observed_at":"2026-08-07T12:45:27.272344Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:27.120365Z","title":"Towards robust vision by multi-task learning on monkey visual cortex.Advances in Neural Information Processing Systems, 34:739–751, 2021","venue":null,"work_id":"9e05e064-c58a-4fff-865d-e22498da8eb4","year":2021},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.422943Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:8aac0653b74117ea225620971c323783dd6a308aedee3ba9247f7cda4a373c59","observation_id":"66f5b308-1578-4810-8178-cf0659017f49","resolution":{"observed_at":"2026-08-07T12:45:27.162794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:27.027668Z","title":"Learning from brains how to regularize machines","venue":null,"work_id":"1c274556-3cd9-4209-a666-503e2955aae7","year":2019},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.480890Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:6937c0b06eb2fb32fd00ed2b2fe79417fc01e1ca10e05a50db20eb18df3e065d","observation_id":"a708170b-d34e-4122-b430-9dbd546cde3e","resolution":{"observed_at":"2026-08-07T12:45:27.066944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01405","last_updated":"2025-03-03T06:14:14Z","snapshot_observed_at":"2026-07-06T16:26:38.284922Z","submitted_at":"2023-10-02T17:59:07Z","title":"Representation Engineering: A Top-Down Approach to AI Transparency","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01405","snapshot_observed_at":"2026-08-07T12:45:21.550320Z","title":"Representation engineering: A top-down approach to ai transparency.arXiv preprint arXiv:2310.01405, 2023","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.550320Z"},"links":{"cited_paper":"/paper/2310.01405","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:65e5ffd92e1701a63601689178613b718c81bf703fb859e5f2efd83299bb326e","observation_id":"ec97fb59-ff5a-45bf-b78c-b946a352786c","resolution":{"observed_at":"2026-08-07T12:45:21.550320Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1606.06565","last_updated":"2016-07-25T17:23:29Z","snapshot_observed_at":"2026-07-06T05:00:46.434335Z","submitted_at":"2016-06-21T13:37:05Z","title":"Concrete Problems in AI Safety","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.06565","snapshot_observed_at":"2026-08-07T12:45:21.621684Z","title":"Concrete problems in ai safety.arXiv preprint arXiv:1606.06565, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.621684Z"},"links":{"cited_paper":"/paper/1606.06565","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:f1e1004520d4e464566a961d535bc8c27ce39964bd13cd8eef32053bace0be31","observation_id":"c70e015d-5374-4350-b2da-8731ad7e5b1c","resolution":{"observed_at":"2026-08-07T12:45:21.621684Z","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":"2026-08-07T12:45:26.945819Z","title":"Goal mis- generalization in deep reinforcement learning","venue":null,"work_id":"66f5f5ca-ca9e-4eed-a9aa-2eefdceecf83","year":2022},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.693606Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:a03467436bf1d6061b8287309105e3c414ee2f11cdfe47ef4174c73d657a79a5","observation_id":"ea377a65-fa1e-4a6d-8e7d-194c78625ac0","resolution":{"observed_at":"2026-08-07T12:45:26.976313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08847","last_updated":"2025-04-27T15:21:29Z","snapshot_observed_at":"2026-07-06T19:31:49.052556Z","submitted_at":"2024-10-11T14:22:44Z","title":"Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.08847","snapshot_observed_at":"2026-08-07T12:45:21.765016Z","title":"Un- intentional unalignment: Likelihood displacement in direct preference optimization.arXiv preprint arXiv:2410.08847, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.765016Z"},"links":{"cited_paper":"/paper/2410.08847","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:10fdcce182c05e6aa3f53bd0be72da2c51369f0fd60badc394beb11792684517","observation_id":"ca1cbd79-ce00-485c-a42d-ae54c34d8b4a","resolution":{"observed_at":"2026-08-07T12:45:21.765016Z","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":"2026-08-07T12:45:21.847785Z","title":"The many faces of robustness: A critical analysis of out-of-distribution generalization","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.847785Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:5a1da169d7fbc8d835c5ba6466c38c2c348c7ebbd3411b39bc21bc0208a18679","observation_id":"b1dfd5b9-4571-4fd1-b06a-3f28083b1220","resolution":{"observed_at":"2026-08-07T12:45:21.847785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.18640","last_updated":"2025-03-06T11:45:40Z","snapshot_observed_at":"2026-07-06T19:39:01.657517Z","submitted_at":"2024-10-24T11:06:29Z","title":"Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.18640","snapshot_observed_at":"2026-08-07T12:45:21.939278Z","title":"Weak-to-strong preference optimization: Stealing reward from weak aligned model.arXiv preprint arXiv:2410.18640, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:21.939278Z"},"links":{"cited_paper":"/paper/2410.18640","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:2e04c657d31636f32b3d98a2dc0278fd136aac1fcdd94312ba95e8b163179fda","observation_id":"8d112cc8-5811-4279-aba8-2e29fe42d0d8","resolution":{"observed_at":"2026-08-07T12:45:21.939278Z","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":"2026-08-07T12:45:26.838958Z","title":"Cartl: Cooperative adversarially-robust transfer learning","venue":null,"work_id":"aa51dd83-04f0-4724-8104-c5b86aaf3499","year":2021},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.020935Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:dc462e82cb5033ab78679a672c3ae7064f4f690b97f0a27cd973e3e66ddaea49","observation_id":"1fa8c276-5433-4d03-aa69-7c78d83ccab2","resolution":{"observed_at":"2026-08-07T12:45:26.875786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:26.747292Z","title":"Twins: A fine-tuning framework for improved transferability of adversarial robustness and generalization","venue":null,"work_id":"2febdd0c-795f-4286-91d3-587847921f83","year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.062394Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:e7ace2a21bff1ad4cb95459e704211e0a56692efc35f5ca1073023a09d1e942f","observation_id":"9c6cc5b1-1d1f-4a9e-bd94-f517b0917874","resolution":{"observed_at":"2026-08-07T12:45:26.793975Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:26.646087Z","title":"Enhancing adversarial contrastive learning via adversarial invariant regularization.Advances in Neural Information Processing Systems, 36:16783–16803, 2023","venue":null,"work_id":"27a02aef-7efb-4709-85be-39830f38a4cf","year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.126483Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:dc318e7a05e8453372f8b07ff4d5e013311df685567a9b3b1d5ae8c330de3d8f","observation_id":"23d90110-e897-4870-87e5-f7e6704987cb","resolution":{"observed_at":"2026-08-07T12:45:26.690297Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:22.176637Z","title":"Adversarially robust generalization requires more data.Advances in neural information processing systems, 31, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.176637Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:d7a28744d333b21f0cd1201d4f7c86b3a5fcf3a758ffec0967599ffdc66e44e5","observation_id":"8119cecd-c08f-43cf-92b4-db696b4a5f06","resolution":{"observed_at":"2026-08-07T12:45:22.176637Z","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":"2026-08-07T12:45:22.228037Z","title":"Overcoming catastrophic forgetting in neural networks.Proceedings of the national academy of sciences, 114(13):3521–3526, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.228037Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:f68c55fce955f6a07ab45b92caa591d98979beffae2f50052f189ec4dc2b152a","observation_id":"1e4ed5a6-2481-4292-9db8-7595b9da6429","resolution":{"observed_at":"2026-08-07T12:45:22.228037Z","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":"2026-08-07T12:45:22.276030Z","title":"Learning without forgetting.IEEE transactions on pattern analysis and machine intelligence, 40(12):2935–2947, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.276030Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:d39e942158c0ce954a003c7e9fcf09b28d5951098f312bf45fef8b427a0312a7","observation_id":"a8c906f3-f8f1-45cc-856a-07ddb76ef4a0","resolution":{"observed_at":"2026-08-07T12:45:22.276030Z","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":"2026-08-07T12:45:26.510018Z","title":"Model compression","venue":null,"work_id":"37415492-b689-47a8-98e7-ceb6b39faa5d","year":2006},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.331733Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:f98f885add8c9ae52a71123e325ca9c1401c94a7b58d3a37df2fabb0adcb3cba","observation_id":"a0edb1da-e406-4d9f-aeab-abe624443bf8","resolution":{"observed_at":"2026-08-07T12:45:26.558778Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-07T12:45:22.406764Z","title":"Distilling the knowledge in a neural network.arXiv preprint arXiv:1503.02531, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.406764Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:2113c5fe4e55bd262f47e228949e3bbf40c13b97d9d9050461d64d9b462da5c2","observation_id":"1ee7b38c-cae3-4e3a-9557-54bfe6888bee","resolution":{"observed_at":"2026-08-07T12:45:22.406764Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6550","last_updated":"2015-03-27T11:52:28Z","snapshot_observed_at":"2026-07-06T04:04:16.777653Z","submitted_at":"2014-12-19T22:40:51Z","title":"FitNets: Hints for Thin Deep Nets","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6550","snapshot_observed_at":"2026-08-07T12:45:22.454227Z","title":"Fitnets: Hints for thin deep nets.arXiv preprint arXiv:1412.6550, 2014","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.454227Z"},"links":{"cited_paper":"/paper/1412.6550","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:32f5ed48c8cd1266c34be2d9d2194e03bb153502232459cf2fb569ff7670577f","observation_id":"96ebfe8a-c792-47af-8ef1-d48d53f1a038","resolution":{"observed_at":"2026-08-07T12:45:22.454227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1612.03928","last_updated":"2017-02-12T22:05:47Z","snapshot_observed_at":"2026-07-06T05:22:25.273447Z","submitted_at":"2016-12-12T21:15:57Z","title":"Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1612.03928","snapshot_observed_at":"2026-08-07T12:45:22.505709Z","title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer.arXiv preprint arXiv:1612.03928, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.505709Z"},"links":{"cited_paper":"/paper/1612.03928","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:d321a355adaa8e340f9e224609d4885c6d64fdf15546e13f406a32d53fd7738f","observation_id":"25f3f62f-4315-4e3f-8dd9-f43199ad7480","resolution":{"observed_at":"2026-08-07T12:45:22.505709Z","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":"2026-08-07T12:45:26.413519Z","title":"Cross modal distillation for supervision transfer","venue":null,"work_id":"6bec9e4d-2f9a-4541-850d-7f5affedd9fd","year":2016},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.565326Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:6cf8cb73607c0a74aef115559ae609e395067e72b835286eab54abdbcded4153","observation_id":"6662bd58-b1b8-4dae-9eb9-8963c9527031","resolution":{"observed_at":"2026-08-07T12:45:26.446303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1808.06670","last_updated":"2019-02-22T18:38:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2018-08-20T19:52:51Z","title":"Learning deep representations by mutual information estimation and maximization","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.06670","snapshot_observed_at":"2026-08-07T12:45:22.619706Z","title":"Learning deep representations by mutual information estimation and maximization","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.619706Z"},"links":{"cited_paper":"/paper/1808.06670","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:3ffdbfe67355320d9ab8f1c0ad8a94b595fba83c9f1aa17a3c5b83ac6fc602fb","observation_id":"39851d30-f6c2-4223-bdbf-572838cf93bf","resolution":{"observed_at":"2026-08-07T12:45:22.619706Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-07-06T08:31:42.308496Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-07T12:45:22.668737Z","title":"Contrastive representation distillation.arXiv preprint arXiv:1910.10699, 2019","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.668737Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:975937aa0d3ca1c923c1e1aca95c7053381509cfc574b3c843a6d035ea396c8f","observation_id":"44a44160-8c68-472e-b887-4b695b087a44","resolution":{"observed_at":"2026-08-07T12:45:22.668737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.06509","last_updated":"2025-09-03T10:31:46Z","snapshot_observed_at":"2026-08-07T16:38:37.859890Z","submitted_at":"2024-09-10T13:41:08Z","title":"Aligning Machine and Human Visual Representations across Abstraction Levels","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.06509","snapshot_observed_at":"2026-08-07T12:45:22.722746Z","title":"Aligning machine and human visual representations across abstraction levels.arXiv preprint arXiv:2409.06509, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.722746Z"},"links":{"cited_paper":"/paper/2409.06509","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:1028325fbcd7264d09666e794c0de95a12f7f7744815f5076a84a5bc0bf9f265","observation_id":"08ef920a-9989-4c2c-9a44-b58297166112","resolution":{"observed_at":"2026-08-07T12:45:22.722746Z","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":"2026-08-07T12:45:22.795513Z","title":"Similarity of neural network representations revisited","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.795513Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:6ebee2ef06fe51af5693f1800e6aea137c9076c5e456cf838ecbc6facc946bec","observation_id":"2853fa05-7b52-4726-8842-05432f3455fd","resolution":{"observed_at":"2026-08-07T12:45:22.795513Z","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":"2026-08-07T12:45:22.836396Z","title":"Improved object recognition using neural networks trained to mimic the brain’s statistical properties.Neural Networks, 131:103–114, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.836396Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:98b8cf8d1614093d479eb98e514d4bdaa45aa869232fedf9a1c74dfe8c171f37","observation_id":"c0022be9-57da-4d39-ad71-3f15d0e5040a","resolution":{"observed_at":"2026-08-07T12:45:22.836396Z","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":"2026-08-07T12:45:22.889165Z","title":"Learning multiple layers of features from tiny images","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.889165Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:fb3867b6e91cdbace0d1d097b9e3676ebdce42b8bfcbec0438a572d34f885342","observation_id":"e20a6d1c-1f2d-43e6-9118-0ae12bd15a6b","resolution":{"observed_at":"2026-08-07T12:45:22.889165Z","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":"2026-08-07T12:45:22.940054Z","title":"Imagenet: A large-scale hierarchical image database","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.940054Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:6e82d6add75dfadd0a973a04a13aa9718a1ec4d6a4e87bbfa138f2832bc540cd","observation_id":"ea0ba0a1-61ba-4f8f-b6b3-b61897db328d","resolution":{"observed_at":"2026-08-07T12:45:22.940054Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.12261","last_updated":"2019-03-28T20:56:37Z","snapshot_observed_at":"2026-08-02T09:01:28.869881Z","submitted_at":"2019-03-28T20:56:37Z","title":"Benchmarking Neural Network Robustness to Common Corruptions and Perturbations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.12261","snapshot_observed_at":"2026-08-07T12:45:22.985620Z","title":"Benchmarking neural network robustness to common corruptions and perturbations.arXiv preprint arXiv:1903.12261, 2019","venue":null,"work_id":null,"year":1903},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.985620Z"},"links":{"cited_paper":"/paper/1903.12261","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:40567946568d4ce4ac0f1a768130a0c116af65f830b49c0cb9de042abfad76aa","observation_id":"5bbef74b-07da-4520-aa84-5ed859d4f8e9","resolution":{"observed_at":"2026-08-07T12:45:22.985620Z","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":"2026-08-07T12:45:23.060438Z","title":"Mobilenetv2: Inverted residuals and linear bottlenecks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.060438Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:4c1d403b90869e033787f4b58a09f78d0dbf03c0fff34c7f87867bbea28f137f","observation_id":"168048b7-a0ea-4c05-a9af-52c9adb38860","resolution":{"observed_at":"2026-08-07T12:45:23.060438Z","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":"2026-08-07T12:45:23.140737Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.140737Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:3b4275fd2e730f0564215878904d4fe4caf35fc7dd170b1acd7d3ea151edceea","observation_id":"fc391679-0535-4ebf-9bca-90aa68624a26","resolution":{"observed_at":"2026-08-07T12:45:23.140737Z","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":"2026-08-07T12:45:23.216380Z","title":"Densely connected convolutional networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.216380Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:949fd399abafac74b2f04452fabb6a7d7ec0f25ca1e13d00a42ca90dc5c344fd","observation_id":"b755eea6-dd6e-4b13-a956-1de50f06d1e3","resolution":{"observed_at":"2026-08-07T12:45:23.216380Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.10054","last_updated":"2022-02-21T09:03:34Z","snapshot_observed_at":"2026-08-04T02:30:25.691953Z","submitted_at":"2022-02-21T09:03:34Z","title":"Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.10054","snapshot_observed_at":"2026-08-07T12:45:23.313490Z","title":"Fine-tuning can distort pretrained features and underperform out-of-distribution.arXiv preprint arXiv:2202.10054, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.313490Z"},"links":{"cited_paper":"/paper/2202.10054","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:6cd81304d84cd3249eb9f508519eed33b13e34157eab332c3cd2ec29e8f8e026","observation_id":"6ffcf445-5eaa-4be4-9946-19b2e5c7a72c","resolution":{"observed_at":"2026-08-07T12:45:23.313490Z","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":"2026-08-07T12:45:23.411236Z","title":"Imagenet classification with deep convolutional neural networks","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.411236Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:f01e50f79fa5d22ecebe22e060a22dfaba5cbfe8bed0c0eadae3a39b73a2e524","observation_id":"73e97f35-0392-4203-b87b-734e0511f83e","resolution":{"observed_at":"2026-08-07T12:45:23.411236Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1610.01644","last_updated":"2018-11-22T23:40:00Z","snapshot_observed_at":"2026-07-06T05:13:30.860932Z","submitted_at":"2016-10-05T20:59:01Z","title":"Understanding intermediate layers using linear classifier probes","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.01644","snapshot_observed_at":"2026-08-07T12:45:23.495814Z","title":"Understanding intermediate layers using linear classifier probes","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.495814Z"},"links":{"cited_paper":"/paper/1610.01644","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:270b18a1c479a2bd1bd8d0a61e4c9b1c253bc11705a2ca63c025b5447c32be5e","observation_id":"8e4bb419-2c6b-4ebb-87fe-22d65f9aa43a","resolution":{"observed_at":"2026-08-07T12:45:23.495814Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.17653","last_updated":"2024-02-26T18:58:43Z","snapshot_observed_at":"2026-08-04T16:43:43.242701Z","submitted_at":"2023-10-26T17:59:46Z","title":"Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model","version":2},"cited_work":{"arxiv_id":"2310.17653","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.17653","snapshot_observed_at":"2026-08-07T12:45:24.527335Z","title":"Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model","venue":"cs.LG","work_id":"36289145-b659-465e-8df6-fb46b0b8e995","year":2023},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.544055Z"},"links":{"cited_paper":"/paper/2310.17653","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:9dd466e7400300eccffbe5d104fe56f223823c178614bc058f8365bc81b39fec","observation_id":"85d8257f-73be-484e-8a04-8c5c25eff178","resolution":{"observed_at":"2026-08-07T12:45:24.587487Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:23.592333Z","title":"Adversarial examples are not bugs, they are features.Advances in neural information processing systems, 32, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.592333Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:dc230d1d2fcb3cc3f9fbd42c4bd824e17fff0ac9374b2ee609ccf67ce878eb6a","observation_id":"3c3b052f-8c24-43fe-ae3f-e9503e3855cd","resolution":{"observed_at":"2026-08-07T12:45:23.592333Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.03771","last_updated":"2020-07-14T03:42:34Z","snapshot_observed_at":"2026-07-06T08:27:58.343233Z","submitted_at":"2019-10-09T03:23:22Z","title":"HuggingFace's Transformers: State-of-the-art Natural Language Processing","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.03771","snapshot_observed_at":"2026-08-07T12:45:23.665315Z","title":"Huggingface’s transformers: State-of-the-art natural language processing.arXiv preprint arXiv:1910.03771, 2019","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.665315Z"},"links":{"cited_paper":"/paper/1910.03771","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:f71f179e0d4b02d0afbf4c4f59df95df5b28c024c151356a261ef93e77c70265","observation_id":"4ca6bd0e-af12-4e06-b4e7-d5356ebe9d84","resolution":{"observed_at":"2026-08-07T12:45:23.665315Z","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":"2026-08-07T12:45:23.757612Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.757612Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:dde0c205966069bd2df441c4a8b54e988abc7d5dea472c7ab97038f1144871e1","observation_id":"4455b4cf-d382-4c9f-bf57-65f5ff8e0594","resolution":{"observed_at":"2026-08-07T12:45:23.757612Z","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":"2026-08-07T12:45:26.114470Z","title":"Boolq: Exploring the surprising difficulty of natural yes/no questions","venue":null,"work_id":"910dc9ef-b138-40a7-bd67-ed902ae4d7e0","year":2019},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.845868Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:50871df36a6f36cf8c76fd478356bab5dddb3b8f21341233fb1acd35d53df533","observation_id":"cd06dcbe-66ad-4a7a-a942-f564d02f55b5","resolution":{"observed_at":"2026-08-07T12:45:26.228433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:25.867413Z","title":"Cosmos QA: Machine reading comprehension with contextual commonsense reasoning","venue":null,"work_id":"13da0c0f-91c9-4652-b293-603e8a30519f","year":2019},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:23.965588Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:da0084be2a09b7aca30e61ad28cd56ce4b769d7f382bcb3a77ca8d9c7dc535cc","observation_id":"c2de80e6-481e-45d2-9214-13c862a346f9","resolution":{"observed_at":"2026-08-07T12:45:25.994940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:25.664558Z","title":"gaussian noise","venue":null,"work_id":"4a21e697-4b5a-4beb-aa2b-0bff70e72412","year":2020},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:24.133875Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:9947703728b7ce74786a3bec54f313f7666b9283b3dfb25e1ccab691ecb5dc0c","observation_id":"ba176370-f3e2-4afb-a051-abbb39fece26","resolution":{"observed_at":"2026-08-07T12:45:25.746774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:25.450201Z","title":"We then evaluate the feature’s correlation with this binary labeling across target dataset images distorted with corruptions from the ImageNet-C benchmark","venue":null,"work_id":"ff300260-393d-45ae-80f5-b792b610030a","year":null},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:24.271275Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:ca52dd1babf0ad89158a305c2dd76548a19cdc91ab541ed6cbe127f5cba40494","observation_id":"b76add17-d659-4fbd-a6bb-34f74aa8aad9","resolution":{"observed_at":"2026-08-07T12:45:25.543784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:25.193470Z","title":"This choice reflects the intuition that a useful feature may be strongly predictive of a subset of classes","venue":null,"work_id":"f7e81648-6f23-4ba4-9199-e15dd4995517","year":null},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:24.334179Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:202b6c1622aa3c1110386a5719a6a9a71f966ff93c7c115f4c36d457f3fdb7c7","observation_id":"31ee302d-1df6-4135-9007-08441006d498","resolution":{"observed_at":"2026-08-07T12:45:25.334070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T12:45:24.953843Z","title":"speckle-noise","venue":null,"work_id":"6fedaf8f-9793-46d5-aa5a-e48b958aea21","year":null},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:24.415140Z"},"links":{"citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:629d6b76796b226cbeec2b46047c3f7932cd7c9a1713cabe9a92c79f2362f8a2","observation_id":"4757b11f-385d-4cc9-adc8-9450c5ce99d8","resolution":{"observed_at":"2026-08-07T12:45:25.046125Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T12:35:50.271238Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation"},"reference_resolution":{"displayed":59,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":39,"verified_exact":1,"verified_fuzzy":18},"total_outbound_references":59},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2505.23933."}