{"as_of":"2026-08-16T08:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:41c1ca391e1f9894d475efd14a8cdf6bab1a56b460579733903f530e92a39e80","coverage":[{"denominator":58,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":58,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:04:12.846995Z","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":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T20:19:26.486227Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-05T20:19:27.572540Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"cited_work":{"arxiv_id":"2505.20313","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.20313","snapshot_observed_at":"2026-08-05T20:19:27.572540Z","title":"Reasoning in Neurosymbolic AI","venue":"cs.AI","work_id":"5fc6e17d-7514-471f-896e-e1babc38e683","year":2025},"citing_paper":{"arxiv_id":"2508.10777","last_updated":"2025-08-14T16:01:10Z","snapshot_observed_at":"2026-08-07T17:34:53.037498Z","submitted_at":"2025-08-14T16:01:10Z","title":"The Knowledge-Reasoning Dissociation: Fundamental Limitations of LLMs in Clinical Natural Language Inference","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-05T20:19:26.486227Z"},"links":{"cited_paper":"/paper/2505.20313","citing_paper":"/paper/2508.10777"},"observation_digest":"sha256:29fb1970dc8fbe06beccea8424de1c396038b7f130e6710a42f56b68e8a1a0e9","observation_id":"4ecfdbbc-f6a9-4e32-9e90-e6925343f69b","resolution":{"observed_at":"2026-08-05T20:19:27.612062Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2505.20313/citation-record","integrity":"/paper/2505.20313/integrity","json":"/paper/2505.20313/citation-record.json","paper":"/paper/2505.20313"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:10.068768Z","title":"Learning to solve circuit-sat: An unsupervised differentiable approach","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.068768Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:68d91f1f980c4659ee060cd281f38c203d227c9b234549d2f8d0edc85b77c8a2","observation_id":"e790779e-38a1-4eda-aef9-b11aa4465d2f","resolution":{"observed_at":"2026-08-07T15:04:10.068768Z","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":"2026-08-07T15:04:10.205950Z","title":"Logic tensor networks","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.205950Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:d223f016d0bf72ed00c1801c5a04be02928d7e5c2979a439ca55278983fac3c8","observation_id":"e0273699-c25e-4765-8d00-fca0572b3c48","resolution":{"observed_at":"2026-08-07T15:04:10.205950Z","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":"2026-08-07T15:04:17.189318Z","title":"Learning optimal chess strategies","venue":null,"work_id":"90a9e74e-8404-4a6f-bc31-25a5ec6a147e","year":1994},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.326315Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:29090009d50bd9cc5303a590aad5cd6d4ec40ada8d5cb54c8aa8fddfc8cd7b64","observation_id":"4eeff2e2-fc5d-4da1-aadc-25c4c39c6340","resolution":{"observed_at":"2026-08-07T15:04:17.216692Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:17.065921Z","title":"Applications of maxsat in data analysis","venue":null,"work_id":"b0b72501-f435-446c-915c-4966372d3e03","year":2015},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.466791Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:81e294f857a63a6ba8d9a709b3fd081c720a241b263a66d9438b565717ee19b7","observation_id":"34b99a46-451c-49a8-9c97-eb1cdffd75a8","resolution":{"observed_at":"2026-08-07T15:04:17.121565Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:17.003309Z","title":"Besold, Artur d’Avila Garcez, Ernesto Jim´ enez-Ruiz, Roberto Confalonieri, Pranava Madhyastha, and Benedikt Wagner, editors","venue":null,"work_id":"2a58a4f1-eb1b-401e-a189-e952114c6a6b","year":2024},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.617281Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:b996fbe9f806d7e05fe516117f00ec6dbddafa90ef7694d2a61c53053dc49dfe","observation_id":"0cd90d73-6f6a-4377-9a77-ecd772440c9c","resolution":{"observed_at":"2026-08-07T15:04:17.034626Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.05390","last_updated":"2017-07-17T20:37:08Z","snapshot_observed_at":"2026-08-14T20:47:05.014857Z","submitted_at":"2017-07-17T20:37:08Z","title":"TensorLog: Deep Learning Meets Probabilistic DBs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.05390","snapshot_observed_at":"2026-08-07T15:04:10.716650Z","title":"Cohen, Fan Yang, and Kathryn Mazaitis","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.716650Z"},"links":{"cited_paper":"/paper/1707.05390","citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:fd64784699ec0c5a87895944c897f94125886ca72a725c1962aa9caf19cc99a6","observation_id":"b0b2fd60-88c1-4088-aa09-e070729c0a3c","resolution":{"observed_at":"2026-08-07T15:04:10.716650Z","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":"2026-08-07T15:04:16.924514Z","title":"d’Anjou, M","venue":null,"work_id":"688438fb-7bc3-4ff3-aaf8-10b507107c31","year":1993},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.758504Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:511b78089999a41292b340e2f3c60f2cd44cfa4a88df0d3d0f8e1eebc194fdc9","observation_id":"3014da01-4cfc-42d0-af5f-eee2b98e7b15","resolution":{"observed_at":"2026-08-07T15:04:16.961040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:16.839261Z","title":"d’Avila Garcez, K","venue":null,"work_id":"300c7ba4-c0a6-41a4-a1de-a17525a34d30","year":2001},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.762706Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:c0842ad7780993dbd0ad9f6a06b544604b2aec0f55d9c0282e4e9c4e554fb31a","observation_id":"82c29847-9a40-4a27-b216-fceb4be0735a","resolution":{"observed_at":"2026-08-07T15:04:16.883176Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:16.728464Z","title":"d’Avila Garcez, L","venue":null,"work_id":"a28de40f-b547-44a8-822d-cee835d7e5a6","year":2009},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.774505Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:936c831bf1850e65f0b45a2e59619c0c89195214683a9066efd4944afb01deb2","observation_id":"d3abc97a-fb5d-4326-94b7-4cb40246ae93","resolution":{"observed_at":"2026-08-07T15:04:16.779215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:16.670000Z","title":"Hypergraph neural networks with logic clauses","venue":null,"work_id":"cd6e07f9-9079-4cef-a108-6fed338aebdf","year":2024},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.833590Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:6e784c0c5d419be0f9efd3448df7f4a84e740bff2ce15faa9d74869b74cd2208","observation_id":"3f3951f1-e816-4db9-88f2-5dddb455ee42","resolution":{"observed_at":"2026-08-07T15:04:16.679153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:16.544182Z","title":"Donadello, L","venue":null,"work_id":"d9cf8b87-5575-438d-a212-789bc3b97353","year":2017},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:10.936536Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:5e817242a57264299cddcc460a46550e2156057d8acd53ac302ff582cb4c8375","observation_id":"d4580091-f1e3-4613-b010-c8e8271f9ebf","resolution":{"observed_at":"2026-08-07T15:04:16.599674Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:16.459392Z","title":"Evans and E","venue":null,"work_id":"88bfd0a9-6b91-4b27-81b7-e1d6522e6671","year":2018},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.011993Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:b65f13979a9ac51a586faf2ff1b00dcd2d1f31cfed87a974f5e53f171fc68e9f","observation_id":"0b367b1c-bc3a-4806-9aa6-71524848809c","resolution":{"observed_at":"2026-08-07T15:04:16.503356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:16.330709Z","title":"Fran¸ ca, G","venue":null,"work_id":"fb813d8f-df8c-417d-bae6-f7d2d0918d5e","year":2014},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.073353Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:8098830cbfac41bab807fd8b96103d188c80e2b73cfa1e296e48cdd7e1b4ab97","observation_id":"e926a148-1ae4-4fb7-ba62-a962d1dea7bc","resolution":{"observed_at":"2026-08-07T15:04:16.368590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:16.257297Z","title":null,"venue":null,"work_id":"e046ad6a-f9aa-4932-8cec-009569c338ed","year":2004},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.133621Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:4bf284ff1e4878c8741e4a769885563ad04b1b29bd8d72be9ede1cf03a5eda16","observation_id":"d558c395-1fc7-4fb3-b6fe-a9fc9796d2ca","resolution":{"observed_at":"2026-08-07T15:04:16.292462Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:16.169125Z","title":null,"venue":null,"work_id":"89a7a32e-a9f6-4d2d-b06c-0613a2d3aeff","year":2023},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.224880Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:0e873322e85d090f6a06b466d6cb79c40ede70040b8d45a6bfbdfda81081873a","observation_id":"94d7356c-c744-49f4-ac12-38d7c5195749","resolution":{"observed_at":"2026-08-07T15:04:16.190675Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:16.108347Z","title":"Ccn+: A neuro-symbolic framework for deep learning with re- quirements","venue":null,"work_id":"bbd10710-98ea-4abe-8ad7-d7e4eb3f8fec","year":null},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.249859Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:16d8bffdd58a76d3d64464e31ef43ce2ec53a3692573e846f12a6f25aa761fd1","observation_id":"6ca48701-d8e5-4367-99e3-df0032eb480b","resolution":{"observed_at":"2026-08-07T15:04:16.160275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.778351Z","title":"Hernandez, F","venue":null,"work_id":"6cf7752f-52a8-45f9-a1a2-0be20f02b93a","year":2001},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.257911Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:53dd92be82fd1019562b1cbe19240ce7daa1c3734f3dad9b41c59d67cfa42d6a","observation_id":"285c2863-777e-4b23-9f2e-b2d8e60f066d","resolution":{"observed_at":"2026-08-07T15:04:15.870954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.684262Z","title":null,"venue":null,"work_id":"0d767453-6255-4b26-b0c1-2bc4270744fa","year":null},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.261871Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:b98ef3a262e9da9ccb8f3b780600ef9ca36a6c7cad782d058ec41baf71627810","observation_id":"287ea1b4-afa4-4bcd-a446-b0c148a7525b","resolution":{"observed_at":"2026-08-07T15:04:15.742600Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.595594Z","title":"Hinton, Simon Osindero, and Yee-Whye Teh","venue":null,"work_id":"59c40e23-b5c0-4978-a172-61317b6aa629","year":2006},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.276472Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:d7d2cc0d45fd7d57504c52bdcf56080167013f7f031d198e0224624e17f0b397","observation_id":"6b84bd89-47be-4851-9956-4af31d0910cd","resolution":{"observed_at":"2026-08-07T15:04:15.636349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.523585Z","title":"Decoding intentions","venue":null,"work_id":"595eb019-ea76-4864-8cfc-1dcd92f4dc8f","year":2023},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.292268Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:877888665c872327005cbd7bf786c04bca178a34b088e7ce9f71cd8a3d755614","observation_id":"60c6adc1-eb3d-43bf-8c23-4adbb85eb31c","resolution":{"observed_at":"2026-08-07T15:04:15.551851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.457450Z","title":"Thinking, fast and slow","venue":null,"work_id":"31793640-8775-47d4-9eae-77bbd3627236","year":2011},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.341905Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:4f6a21515cd2473bb6515db0e76aed06e77fd790001b09f350b6f2ec680e7cd9","observation_id":"b9efacaf-6796-477f-8a7e-f2ae26ed6eb7","resolution":{"observed_at":"2026-08-07T15:04:15.485752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.337246Z","title":"Finding pre-production vehicle configurations using a maxsat framework","venue":null,"work_id":"a6c1ce5f-fde1-473d-a322-fbec3c666ee2","year":2016},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.444331Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:053514a68c60f211953e3e2dfed00f4611c8d74db41c9ae1133f605f44f225d9","observation_id":"62fec922-7bc7-4635-b38e-b2ca664a61c1","resolution":{"observed_at":"2026-08-07T15:04:15.416009Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.245761Z","title":"King, Michael J","venue":null,"work_id":"be2cd42f-7e98-4b2b-b324-90fd347db3a8","year":1995},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.520828Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:69086114c2f04ec023e5e19c37e5d30433ef787c3212459b640d5e7415efbc29","observation_id":"0765c195-0440-48d7-800c-1fe46aa55611","resolution":{"observed_at":"2026-08-07T15:04:15.285140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:11.599752Z","title":"Kirkpatrick, C","venue":null,"work_id":null,"year":1983},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.599752Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:4f018a0e64a59b68ef01ba6b28c00a315bb64be6b4c35d2bbd917604ed344a1f","observation_id":"b2abaacf-fc6e-4281-b362-b31c69f3ff8f","resolution":{"observed_at":"2026-08-07T15:04:11.599752Z","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":"2026-08-07T15:04:15.200626Z","title":"Learning max-sat from contextual examples for combinatorial optimisation","venue":null,"work_id":"70eff14d-e18f-46e8-ad5b-f2565105b090","year":2020},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.673215Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:d773a09d7513651fcd15933b802ac95ecf514e0455528dc8b5881a3c6c78e7c9","observation_id":"21fd740d-4ad0-4c7d-a829-fda091500247","resolution":{"observed_at":"2026-08-07T15:04:15.228668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.104888Z","title":"Learning algorithms for the classification restricted boltzmann machine","venue":null,"work_id":"cd67a81d-99b7-49bc-a747-53ede8f96f6e","year":2012},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.746542Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:5a82d7c611086297f258383881fa7bb7939befebdd3d10a7c31ed0d15b7e06a7","observation_id":"d761cff3-5ac6-4744-a043-8f3febae3522","resolution":{"observed_at":"2026-08-07T15:04:15.151682Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.023002Z","title":"Can graph neural networks learn to solve the maxsat problem? (student abstract)","venue":null,"work_id":"cb311253-8c4f-42eb-8906-4c4b92737432","year":2023},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.764094Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:01eda085009dcf8e58707aa757264af2cd2eba10875c0b2d5a1114a519fa5737","observation_id":"a35faf38-d843-4340-8552-c50189a9c9df","resolution":{"observed_at":"2026-08-07T15:04:15.060928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.936081Z","title":null,"venue":null,"work_id":"cd0f6a78-c39b-46c5-aca0-75f33cb75a5a","year":2018},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.767930Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:526aea07da342c3b07c15fa649b771318a1d0addca7093b618862fb538035ec9","observation_id":"fb8da4fa-981e-4676-b5ba-720a668911ff","resolution":{"observed_at":"2026-08-07T15:04:14.975739Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.868081Z","title":"DeepProbLog: Neural probabilistic logic pro- gramming","venue":null,"work_id":"2f8ab05e-0390-4aa3-b408-4154af5418c9","year":2018},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.771999Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:f5b16ce7469428d8c7556147e7035ab488f9f9b46712c9d6c2f123dcfe534d82","observation_id":"1ea8a9b1-4721-4cd7-811b-ac359c80fa4f","resolution":{"observed_at":"2026-08-07T15:04:14.924491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.761814Z","title":"Chip War: The Fight for the World’s Most Critical Technol- ogy","venue":null,"work_id":"fdc25b3b-6190-4b90-a943-090c08b34e7c","year":2022},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.795002Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:e61d839a207dbb576280617abdc62791cf95fbe05db79ab67e421f2121bce6db","observation_id":"fe776c0c-049b-407b-b7bd-d1bc4ecf1228","resolution":{"observed_at":"2026-08-07T15:04:14.793444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.690214Z","title":"Gsm-symbolic: Understanding the limi- tations of mathematical reasoning in large language models, 2024","venue":null,"work_id":"cadd3ddd-6d50-4b4e-acda-f44f393a9e82","year":2024},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.843707Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:fd0adb16b86cb1e866a332b675a18981e1cdc5de4101ff3fc34843fa262feffe","observation_id":"f90c2ee5-8174-4d6c-9eb2-07594781958d","resolution":{"observed_at":"2026-08-07T15:04:14.721171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.614184Z","title":"Maxsat-based mcs enumeration","venue":null,"work_id":"0829d78a-4f14-44bb-9620-4e9a2013972c","year":2013},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.916827Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:af32e4e2ab16b907b4f22073ae5b4bd185f6057597a1f0eec62c392eb66a4fa8","observation_id":"b315aad7-8cd0-4670-a210-c5f8ea2ed896","resolution":{"observed_at":"2026-08-07T15:04:14.645570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.508965Z","title":"Closing the neural-symbolic cycle: Knowledge extraction, user intervention and distillation from convolutional neural net- works","venue":null,"work_id":"1b9654fd-86d3-485b-a675-289585cc389c","year":2023},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.012092Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:1b4de3bcfc3f8ac47e0bf9276c1136e02108bd88713f29cd1bb6e667d08755d8","observation_id":"ae0de1c4-6058-4098-9203-a92e88efa25f","resolution":{"observed_at":"2026-08-07T15:04:14.567758Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.422234Z","title":"A semantic framework for neu- rosymbolic computation","venue":null,"work_id":"eaf0e39f-7928-4f69-8a9a-5c4b97929238","year":2025},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.106190Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:1e792edcc3f34b966d4db1b446c851fc8d46d6caade23fc5a4766443caf39473","observation_id":"db6b3d60-ad73-442f-9fbd-57cf638d7b70","resolution":{"observed_at":"2026-08-07T15:04:14.435282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.373772Z","title":"de Penning, A","venue":null,"work_id":"961a544e-7636-4c49-9efc-8d35cc091da1","year":2011},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.146792Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:7bafaea6b201b3ff2734b66a1276b73791a6041b8e63815650c2b8ea3201ec0e","observation_id":"d5066f33-dae7-45ff-ae32-1f0e48b22216","resolution":{"observed_at":"2026-08-07T15:04:14.405793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.09232","last_updated":"2021-10-08T16:37:11Z","snapshot_observed_at":"2026-08-15T18:40:08.854310Z","submitted_at":"2021-10-08T16:37:11Z","title":"Accountability in AI: From Principles to Industry-specific Accreditation","version":1},"cited_work":{"arxiv_id":"2110.09232","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.09232","snapshot_observed_at":"2026-08-07T15:04:12.991980Z","title":"Accountability in AI: From Principles to Industry-specific Accreditation","venue":"cs.CY","work_id":"9933f38b-d603-4c21-9fe7-e13607fa29a2","year":2021},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.150491Z"},"links":{"cited_paper":"/paper/2110.09232","citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:2660be6ce661b816cd44f168b02c08ca97cfffa0adf6678d2a6fa2353afc5beb","observation_id":"e6a7d9c5-6e78-48f9-a582-0cff947a8958","resolution":{"observed_at":"2026-08-07T15:04:13.014353Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.259048Z","title":null,"venue":null,"work_id":"43deaf23-f845-48dd-98e2-a34743e02862","year":1995},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.154857Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:be38ae7d14997bff04d77b45e503af754eae0d4bce0e0cd0398281625b1756a2","observation_id":"fc2304a7-fda1-4b8c-bcde-dc692cdc9bea","resolution":{"observed_at":"2026-08-07T15:04:14.289591Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.198461Z","title":"Symmetric neural networks and propositional logic satisfia- bility","venue":null,"work_id":"a7732231-4c97-4ebe-b147-430d9f9bc578","year":1991},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.209665Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:4ee23388fb851eeff432f006dc45f872760414ccff9f73054ab1066306136552","observation_id":"aed4d883-43c3-427d-b16f-0dc961312a69","resolution":{"observed_at":"2026-08-07T15:04:14.222030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.125616Z","title":"Markov logic networks","venue":null,"work_id":"907161f4-965d-4b92-99ff-087c2b7d2a2a","year":2006},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.289347Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:f41bf23fbacb522f8aa7efce5e322ae51a7424541d6fd0f0cf62457f7257b5cb","observation_id":"b6094f61-15ab-45ef-9971-fabbafff20f9","resolution":{"observed_at":"2026-08-07T15:04:14.163362Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:14.053452Z","title":null,"venue":null,"work_id":"4acda56b-7b56-4c70-a927-0962b70fdcad","year":2019},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.342267Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:0f3b2f10c83ffa1854535667ab4d32acf74b91aa55dca9788fae943c957f488d","observation_id":"25d45746-a8c2-47ba-8d96-29e1dfe7f8f5","resolution":{"observed_at":"2026-08-07T15:04:14.075692Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.966963Z","title":"Learning and reasoning with logic tensor networks","venue":null,"work_id":"6af19f8a-f415-4f0d-8a69-4074e1ecfa20","year":2016},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.371211Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:7863322f5eaaba0f39b7f26d03abec24b73e47c4904160daf9d14adaf48adc0c","observation_id":"b095399c-ef15-4d0d-8115-156b0ea77045","resolution":{"observed_at":"2026-08-07T15:04:14.024870Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17493","last_updated":"2024-04-14T05:20:10Z","snapshot_observed_at":"2026-08-05T16:03:40.517679Z","submitted_at":"2023-05-27T15:10:41Z","title":"The Curse of Recursion: Training on Generated Data Makes Models Forget","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.17493","snapshot_observed_at":"2026-08-07T15:04:12.416431Z","title":"The curse of recursion: Training on generated data makes models forget","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.416431Z"},"links":{"cited_paper":"/paper/2305.17493","citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:1cebb9b05ed4ba00042cc189549cf2e735b456989fd9ee86005fe002ea42f342","observation_id":"41f5f19d-524a-4129-bcb2-58c052eb446c","resolution":{"observed_at":"2026-08-07T15:04:12.416431Z","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":"2026-08-07T15:04:13.869164Z","title":"Maximum satisfiabil- ity in software analysis: Applications and techniques","venue":null,"work_id":"633f71b5-01d2-42b0-83f1-1982cdb1e494","year":2017},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.450807Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:8fef29f49ac46cee2f6ffff588df9aed189529ae2606eb452a7dac320490da37","observation_id":"3801bac3-1feb-4396-9bbb-3984877a3af7","resolution":{"observed_at":"2026-08-07T15:04:13.891135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.850960Z","title":"Smolensky","venue":null,"work_id":"f2c28613-31f8-454e-98b9-3745ea6f84c5","year":1995},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.492924Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:0cea58032139c8d8775ad18949372a9e4da4a054bcb726c756390d48b7644ced","observation_id":"d91197ba-d802-4c30-9f4a-62d09e6d96e3","resolution":{"observed_at":"2026-08-07T15:04:13.856758Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.808455Z","title":"Bioinformatics: Problem Solving Paradigms","venue":null,"work_id":"2c4e9d57-7d53-4e46-8c13-f9b27ce5fc86","year":2008},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.532156Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:b78c9d7b018034fc9347ddce966e962dc1c72f3c52ca4392d3476b937bb42c87","observation_id":"b3d08f80-5852-4e35-b3c3-55ecdb4d023e","resolution":{"observed_at":"2026-08-07T15:04:13.841364Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.734402Z","title":"Srinivasan","venue":null,"work_id":"6a758838-46d2-4f0c-8512-c6068b556a41","year":2007},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.563975Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:12f8a60589b7235c4226a7f852c44c47967a0e0f0877e3a9e721a8b534991f75","observation_id":"0f26c7de-e946-41e3-b0ac-58c82ebc3025","resolution":{"observed_at":"2026-08-07T15:04:13.771015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.662040Z","title":"Srinivasan, S","venue":null,"work_id":"ea0ad256-883d-4980-af23-99e1827e21d3","year":1994},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.606985Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:7a6a55eb88cab99cc2afa8a25bb95bb97d08096d06d1fcae9165a471977cf342","observation_id":"667808e9-eefa-4f67-b272-8c7e0c62d8ba","resolution":{"observed_at":"2026-08-07T15:04:13.694994Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.09949","last_updated":"2024-10-24T12:13:54Z","snapshot_observed_at":"2026-08-15T02:18:43.854824Z","submitted_at":"2024-06-14T11:52:09Z","title":"Neural Concept Binder","version":2},"cited_work":{"arxiv_id":"2406.09949","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.09949","snapshot_observed_at":"2026-08-07T15:04:12.910148Z","title":"Neural Concept Binder","venue":"cs.AI","work_id":"c70b7209-0f14-4fea-816a-c0b6f6371d33","year":2024},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.634529Z"},"links":{"cited_paper":"/paper/2406.09949","citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:56b27f9e3eacc323fd46ecd8a061fe8af51207ebb757d5a2fd58dd210cd9060f","observation_id":"586dd05c-2e80-4951-b345-c6716cc5f820","resolution":{"observed_at":"2026-08-07T15:04:12.937729Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.587516Z","title":"Towell and J","venue":null,"work_id":"bd8674d0-d891-4239-b175-a3e29864ce0e","year":1994},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.670432Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:a103581d30b13e3d9612c793d26773767185a476df9468917cb3d7d8bcee59c2","observation_id":"cd25e1e7-4af6-43d2-87ab-4f82f595a5e6","resolution":{"observed_at":"2026-08-07T15:04:13.621184Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.497793Z","title":"Tran and A","venue":null,"work_id":"4c970241-8c61-499c-a55c-0e048ed2482e","year":2018},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.687102Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:c7bee162105f7be936acd4a2bfe756202fe73a37bfeedfa317b795a1ff733e74","observation_id":"80f90590-15c5-4855-b6f1-43ea4510eaef","resolution":{"observed_at":"2026-08-07T15:04:13.539375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.410404Z","title":null,"venue":null,"work_id":"506f36ef-355e-4787-81fa-22942bec6c98","year":2021},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.698517Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:5e6a97bb2c8f2ef97ac1170e07042fae74576b606e3a4b1a608d44599d5eb9cb","observation_id":"200d683b-ba71-43f9-b37b-3d8e7120b6b3","resolution":{"observed_at":"2026-08-07T15:04:13.450947Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.329513Z","title":"Tran and Artur d’Avila Garcez","venue":null,"work_id":"7241320c-5ded-40da-bb6e-1ef80e75cf91","year":2023},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.706228Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:9d7370376373232f7524083a0c7f0c4f6ac12fdb483927d8d134866fa4a3b9c5","observation_id":"1ee81454-568d-4f95-b0ff-2de1493c274c","resolution":{"observed_at":"2026-08-07T15:04:13.358029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.271233Z","title":"Donti, Bryan Wilder, and J","venue":null,"work_id":"7cafe8cf-4a44-45b7-b784-74848fc69679","year":2019},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.712223Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:1ab019c14ec845779dcc421b5ba28fc003b8282ae997c364a712a24a29845539","observation_id":"1e6c6f0a-aa73-489f-8fec-c202d6709bb1","resolution":{"observed_at":"2026-08-07T15:04:13.292078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.252162Z","title":"Solving maxsat with matrix multiplication, 2023","venue":null,"work_id":"58059623-7dec-49d8-8c13-9b4a2e8972a3","year":2023},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.731945Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:c5c61b68e348e52d05a97d7d7e4ab90fd23723b0593e38385e915537e3aebd89","observation_id":"8e50341f-82a2-4c49-a795-43a2016c65db","resolution":{"observed_at":"2026-08-07T15:04:13.259388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.207058Z","title":"Generalized simulated annealing algorithm and its application to the thomson model","venue":null,"work_id":"5e895a67-06d5-4ffc-b94d-e985f7722dec","year":1997},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.776700Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:24d134af0874295cbdc1e8d7e9915f8a8a46f94181044f1bc7bf36e5ca62fb1d","observation_id":"01b94831-d446-41a8-87e8-7daeb86f974b","resolution":{"observed_at":"2026-08-07T15:04:13.235412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.132228Z","title":"Differentiable learning of logical rules for knowledge base reasoning","venue":null,"work_id":"6deb6e55-b703-4340-a425-a184b35e4416","year":null},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.811922Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:faac977f373b97f13565e924e7661364415b263ad2bce3c7c6833e642a545660","observation_id":"0ea0dcc1-558c-4e59-8702-958178e8b1a9","resolution":{"observed_at":"2026-08-07T15:04:13.164611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:15.991164Z","title":null,"venue":null,"work_id":"2ee9d281-8dd2-4197-a89d-bbdff48a000f","year":null},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:11.254322Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:f0b98ca4eb692b9542d2735119cf0a01ace669692a04d14d4659a816f6f77137","observation_id":"87d8d174-4c8b-45d9-846f-93dd6fea6c2b","resolution":{"observed_at":"2026-08-07T15:04:16.071011Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T15:04:13.062598Z","title":null,"venue":null,"work_id":"34f50304-fb4e-43b8-827b-5d324da29768","year":2017},"citing_paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI","version":1},"reference_index":2328,"source":"pdf_text","source_observed_at":"2026-08-07T15:04:12.846995Z"},"links":{"citing_paper":"/paper/2505.20313"},"observation_digest":"sha256:b4444554710023e3909b4f05d3b9fc8fc56f8abbfc4a1055ee07aa54f95cf8bf","observation_id":"d9c1edb5-56fd-42ac-af99-6eb44d8e13b9","resolution":{"observed_at":"2026-08-07T15:04:13.095658Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.20313","last_updated":"2025-05-22T11:57:04Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-09T13:02:08.613645Z","submitted_at":"2025-05-22T11:57:04Z","title":"Reasoning in Neurosymbolic AI"},"reference_resolution":{"displayed":58,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":2,"verified_fuzzy":42},"total_outbound_references":58},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2505.20313."}