{"as_of":"2026-08-08T12:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:49554035873f7cb27a1122a2ee3f1faaca7dba569beff971a31baa6191630c5f","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T08:29:36.699879Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.22748/citation-record","integrity":"/paper/2607.22748/integrity","json":"/paper/2607.22748/citation-record.json","paper":"/paper/2607.22748"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T08:29:35.038272Z","title":"Neural reuse: A fundamental organizational principle of the brain","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.038272Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:622a95da4fd6d3a018b0e6b1bd297601af3e275f584eceda9b94c4bd80a3db18","observation_id":"5690f267-3c67-40fd-a0a5-da3310b28816","resolution":{"observed_at":"2026-08-01T08:29:35.038272Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.01261","last_updated":"2018-10-17T17:51:36Z","snapshot_observed_at":"2026-07-06T06:42:54.610341Z","submitted_at":"2018-06-04T17:58:18Z","title":"Relational inductive biases, deep learning, and graph networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.01261","snapshot_observed_at":"2026-08-01T08:29:35.093329Z","title":"Relational inductive biases, deep learning, and graph networks.arXiv preprint arXiv:1806.01261, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.093329Z"},"links":{"cited_paper":"/paper/1806.01261","citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:15abf7ac0c37004fd60b1dfaccd38af98ba3941839e1c78b64cca23ac43f7344","observation_id":"31bcc8bc-1c4e-4d5c-b8f1-782db8ef119e","resolution":{"observed_at":"2026-08-01T08:29:35.093329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1308.3432","last_updated":"2013-08-15T15:19:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-08-15T15:19:34Z","title":"Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1308.3432","snapshot_observed_at":"2026-08-01T08:29:35.172397Z","title":"Estimating or propagat- ing gradients through stochastic neurons for conditional computation.arXiv preprint arXiv:1308.3432, 2013","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.172397Z"},"links":{"cited_paper":"/paper/1308.3432","citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:8832b0ab8919a29323d89f4c2b5c03735f573b8d0a03376c9b1610be85842684","observation_id":"17294080-f8f2-4f15-8b72-507326ec0ff8","resolution":{"observed_at":"2026-08-01T08:29:35.172397Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.07258","last_updated":"2022-07-12T23:45:14Z","snapshot_observed_at":"2026-08-02T09:20:40.804790Z","submitted_at":"2021-08-16T17:50:08Z","title":"On the Opportunities and Risks of Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.07258","snapshot_observed_at":"2026-08-01T08:29:35.225814Z","title":"On the opportunities and risks of foundation models.arXiv preprint arXiv:2108.07258, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.225814Z"},"links":{"cited_paper":"/paper/2108.07258","citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:ecf624039cd52c7ed3b522dc85c063827138894f6bd6e85eb264e7d1142de7f2","observation_id":"9968e45e-75f9-4401-9578-ee0ae4a1d537","resolution":{"observed_at":"2026-08-01T08:29:35.225814Z","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":"2026-08-01T08:29:35.301126Z","title":"Language models are few-shot learners.Advances in neural information processing sys- tems, 33:1877–1901, 2020","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.301126Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:00cb685add51f17236f6b75cd41b4a509a6ffdb6d0bcb516a6de987f95548248","observation_id":"44e85dd7-89d0-4dd4-ad97-04cb45defaad","resolution":{"observed_at":"2026-08-01T08:29:35.301126Z","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":"2026-08-01T08:29:35.360696Z","title":"Parameter-efficient fine-tuning of large-scale pre-trained language models.Nature machine intelligence, 5(3):220–235, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.360696Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:a05ffc9db0a0fb087eccd70689e55674fc0ef202c5189e7bda6d4499d0eb7bce","observation_id":"804babca-75ae-4fb1-b640-a4f691e67c98","resolution":{"observed_at":"2026-08-01T08:29:35.360696Z","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":"2026-08-01T08:29:35.415798Z","title":"Neuroscience-inspired artificial intelligence.Neuron, 95(2):245–258, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.415798Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:82d41ed0a44fb972219743221dc370cc6483f6f1b3208f17725db66fb1d93b19","observation_id":"ef286b1a-95f2-4967-9984-3847728802cb","resolution":{"observed_at":"2026-08-01T08:29:35.415798Z","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":"2026-08-01T08:29:35.479073Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.479073Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:200168231c5cfa4d05793b2dcab88b89bb33a2c5d3fef6a3c8d47063e20e3ecb","observation_id":"d4cb1209-444d-4fd0-b5aa-901c7fa871ac","resolution":{"observed_at":"2026-08-01T08:29:35.479073Z","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":"2026-08-01T08:29:35.534452Z","title":"Experience-dependent structural synaptic plas- ticity in the mammalian brain.Nature Reviews Neuroscience, 10(9):647–658, 2009","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.534452Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:30a05a2fa3bddbd0534350b2ee3ad84be7800b16b3c78e19a114221650169338","observation_id":"11d0e2cb-f5f9-44e2-b5bc-1b0a31e45797","resolution":{"observed_at":"2026-08-01T08:29:35.534452Z","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":"2026-08-01T08:29:35.641781Z","title":"Parameter- efficient transfer learning for nlp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.641781Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:ad676a30f95409601d12a357b32dc042d6679d36e450231b185a25ed5aa39e64","observation_id":"05bd98cf-cae3-4ee3-8013-785b27bfb185","resolution":{"observed_at":"2026-08-01T08:29:35.641781Z","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":"2026-08-01T08:29:35.712606Z","title":"Lora: Low-rank adaptation of large language models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.712606Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:23cbc25de5bc158e011c9cb96f80fb60239c72df05d129ccb88678e7ec9d769e","observation_id":"4de70032-08df-4fa3-999b-d62b2ba189d9","resolution":{"observed_at":"2026-08-01T08:29:35.712606Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.02907","last_updated":"2017-02-22T09:55:36Z","snapshot_observed_at":"2026-07-06T05:10:16.862707Z","submitted_at":"2016-09-09T19:48:41Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.02907","snapshot_observed_at":"2026-08-01T08:29:35.765200Z","title":"Semi-supervised classification with graph convolu- tional networks.arXiv preprint arXiv:1609.02907, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.765200Z"},"links":{"cited_paper":"/paper/1609.02907","citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:17fa32e30f8943f703f51fe76399454677a6a9dd96bd6892f34f903492cc6995","observation_id":"43b5a802-ca22-42d9-9061-fb20fb194bd5","resolution":{"observed_at":"2026-08-01T08:29:35.765200Z","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":"2026-08-01T08:29:35.846751Z","title":"Deep learning.nature, 521(7553):436–444, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.846751Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:970d5fec92f8e09be67616b3676623422384b700f68dac4c18555c97ea65858e","observation_id":"f433d482-c8b5-4d0d-b145-ee8ded6f1db2","resolution":{"observed_at":"2026-08-01T08:29:35.846751Z","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":"2026-08-01T08:29:35.956698Z","title":"Synaptic plasticity forms and functions","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:35.956698Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:fd5b6be1c2a27ea45a8253c456428b4089a916b477d538e6e15c3d49816ccffc","observation_id":"563e401f-29c0-451d-827d-90561f72be09","resolution":{"observed_at":"2026-08-01T08:29:35.956698Z","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":"2026-08-01T08:29:36.015257Z","title":"Cellular, synaptic and network effects of neuro- modulation.Neural Networks, 15(4-6):479–493, 2002","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:36.015257Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:c0394de888cb422cdf8143beb7953c8b28ca806b09d8f58e85faec2860655fff","observation_id":"ea8901e1-2614-4f70-acb8-2ba4cb3a0995","resolution":{"observed_at":"2026-08-01T08:29:36.015257Z","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":"2026-08-01T08:29:36.096807Z","title":"Human-level control through deep reinforcement learning.nature, 518(7540):529–533, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:36.096807Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:79bc61d9e13660359e2e9a985f972212059db9b675d7051264d37c9de1a1bbab","observation_id":"77455b1b-f621-4ff7-b187-ce16497a1c3d","resolution":{"observed_at":"2026-08-01T08:29:36.096807Z","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":"2026-08-01T08:29:36.209906Z","title":"Continual lifelong learning with neural networks: A review.Neural networks, 113:54–71, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:36.209906Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:bdba3d60af79e7d84ebf7124626cd1a5def3cde2e2e8499ac57c9e7cca2a5aa4","observation_id":"0c8d124c-f107-443e-826a-651386e14efb","resolution":{"observed_at":"2026-08-01T08:29:36.209906Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.11529","last_updated":"2024-01-27T12:01:57Z","snapshot_observed_at":"2026-07-06T14:54:41.337108Z","submitted_at":"2023-02-22T18:11:25Z","title":"Modular Deep Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.11529","snapshot_observed_at":"2026-08-01T08:29:36.316848Z","title":"Modular deep learning.arXiv preprint arXiv:2302.11529, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:36.316848Z"},"links":{"cited_paper":"/paper/2302.11529","citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:ecb0faa4aff5bd8c710fcce17e34541cd0d7dbedbd898ee05adae6c559a2e2fd","observation_id":"177728ac-af27-4248-ab42-ad8691f39ddd","resolution":{"observed_at":"2026-08-01T08:29:36.316848Z","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":"2026-08-01T08:29:36.464610Z","title":"A deep learning framework for neuroscience.Nature neuroscience, 22(11):1761–1770, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:36.464610Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:ea09b480f04559a4451139ee1250cad522af5db55a301c3b69e8f0e8bffea821","observation_id":"3803fabb-3381-4070-a4bb-c95f0241108c","resolution":{"observed_at":"2026-08-01T08:29:36.464610Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.01239","last_updated":"2017-12-31T14:53:00Z","snapshot_observed_at":"2026-08-05T10:32:12.591894Z","submitted_at":"2017-11-03T17:07:51Z","title":"Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.01239","snapshot_observed_at":"2026-08-01T08:29:36.543882Z","title":"Routing networks: Adaptive selection of non-linear functions for multi-task learning.arXiv preprint arXiv:1711.01239, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:36.543882Z"},"links":{"cited_paper":"/paper/1711.01239","citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:eadef5c389696807140385d4ad8a170ad4cd696b1cb52d670e55d7732f5fd14f","observation_id":"a4a4e044-eb33-4b6e-b815-72f3df1f4c7e","resolution":{"observed_at":"2026-08-01T08:29:36.543882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1701.06538","last_updated":"2017-01-23T18:10:00Z","snapshot_observed_at":"2026-07-06T05:27:13.416519Z","submitted_at":"2017-01-23T18:10:00Z","title":"Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1701.06538","snapshot_observed_at":"2026-08-01T08:29:36.624144Z","title":"Outrageously large neural networks: The sparsely-gated mixture- of-experts layer.arXiv preprint arXiv:1701.06538, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:36.624144Z"},"links":{"cited_paper":"/paper/1701.06538","citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:b51135209c5a2ca78de49ceba3b7c14c65712c22554252cf9228fecf70d266ef","observation_id":"7ea366d9-1b01-4564-8606-fe7ad545bb76","resolution":{"observed_at":"2026-08-01T08:29:36.624144Z","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":"2026-08-01T08:29:36.699879Z","title":"Attention is all you need.Advances in neural information processing systems, 30, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T08:29:36.699879Z"},"links":{"citing_paper":"/paper/2607.22748"},"observation_digest":"sha256:00079560536fd7bcb2e593abc0d56bca0460db88176706fdd671e6d3c5c45741","observation_id":"720f2488-5494-451c-b971-8670caefe211","resolution":{"observed_at":"2026-08-01T08:29:36.699879Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.22748","last_updated":"2026-07-23T09:48:11Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T22:36:48.276721Z","submitted_at":"2026-07-23T09:48:11Z","title":"Learning to Access Computation: Accessibility Plasticity as a Principle of Adaptive Intelligence"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":22,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":22},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.22748."}