{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:67T4Q7N6PFJCUOCKDIS7TQ4YCM","short_pith_number":"pith:67T4Q7N6","schema_version":"1.0","canonical_sha256":"f7e7c87dbe79522a384a1a25f9c398133c70a7c6c359adb4a578b52be5ed59c3","source":{"kind":"arxiv","id":"2507.14747","version":1},"attestation_state":"computed","paper":{"title":"Pruning Increases Orderedness in Recurrent Computation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.LG","authors_text":"Yiding Song","submitted_at":"2025-07-19T20:44:17Z","abstract_excerpt":"Inspired by the prevalence of recurrent circuits in biological brains, we investigate the degree to which directionality is a helpful inductive bias for artificial neural networks. Taking directionality as topologically-ordered information flow between neurons, we formalise a perceptron layer with all-to-all connections (mathematically equivalent to a weight-tied recurrent neural network) and demonstrate that directionality, a hallmark of modern feed-forward networks, can be induced rather than hard-wired by applying appropriate pruning techniques. Across different random seeds our pruning sch"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2507.14747","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-07-19T20:44:17Z","cross_cats_sorted":["cs.NE"],"title_canon_sha256":"6c13f6c8d85b61d4c123162500864d5dc663680cc56712a848d3804a0b495afa","abstract_canon_sha256":"c292acfa082fa9be6801264bbe87d154c4bb0f52c199c96030977fa2cf139771"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:40:12.802238Z","signature_b64":"HvZtSjmT0T4310FBBuughmeojPmuOQBa20J7s6Xos+JbQUG6fL8E6vqmykPyQznbOQQiGuU6vnA51V0u1qA+BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f7e7c87dbe79522a384a1a25f9c398133c70a7c6c359adb4a578b52be5ed59c3","last_reissued_at":"2026-07-05T11:40:12.801697Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:40:12.801697Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Pruning Increases Orderedness in Recurrent Computation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.NE"],"primary_cat":"cs.LG","authors_text":"Yiding Song","submitted_at":"2025-07-19T20:44:17Z","abstract_excerpt":"Inspired by the prevalence of recurrent circuits in biological brains, we investigate the degree to which directionality is a helpful inductive bias for artificial neural networks. Taking directionality as topologically-ordered information flow between neurons, we formalise a perceptron layer with all-to-all connections (mathematically equivalent to a weight-tied recurrent neural network) and demonstrate that directionality, a hallmark of modern feed-forward networks, can be induced rather than hard-wired by applying appropriate pruning techniques. Across different random seeds our pruning sch"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.14747","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2507.14747/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2507.14747","created_at":"2026-07-05T11:40:12.801764+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.14747v1","created_at":"2026-07-05T11:40:12.801764+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.14747","created_at":"2026-07-05T11:40:12.801764+00:00"},{"alias_kind":"pith_short_12","alias_value":"67T4Q7N6PFJC","created_at":"2026-07-05T11:40:12.801764+00:00"},{"alias_kind":"pith_short_16","alias_value":"67T4Q7N6PFJCUOCK","created_at":"2026-07-05T11:40:12.801764+00:00"},{"alias_kind":"pith_short_8","alias_value":"67T4Q7N6","created_at":"2026-07-05T11:40:12.801764+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/67T4Q7N6PFJCUOCKDIS7TQ4YCM","json":"https://pith.science/pith/67T4Q7N6PFJCUOCKDIS7TQ4YCM.json","graph_json":"https://pith.science/api/pith-number/67T4Q7N6PFJCUOCKDIS7TQ4YCM/graph.json","events_json":"https://pith.science/api/pith-number/67T4Q7N6PFJCUOCKDIS7TQ4YCM/events.json","paper":"https://pith.science/paper/67T4Q7N6"},"agent_actions":{"view_html":"https://pith.science/pith/67T4Q7N6PFJCUOCKDIS7TQ4YCM","download_json":"https://pith.science/pith/67T4Q7N6PFJCUOCKDIS7TQ4YCM.json","view_paper":"https://pith.science/paper/67T4Q7N6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.14747&json=true","fetch_graph":"https://pith.science/api/pith-number/67T4Q7N6PFJCUOCKDIS7TQ4YCM/graph.json","fetch_events":"https://pith.science/api/pith-number/67T4Q7N6PFJCUOCKDIS7TQ4YCM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/67T4Q7N6PFJCUOCKDIS7TQ4YCM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/67T4Q7N6PFJCUOCKDIS7TQ4YCM/action/storage_attestation","attest_author":"https://pith.science/pith/67T4Q7N6PFJCUOCKDIS7TQ4YCM/action/author_attestation","sign_citation":"https://pith.science/pith/67T4Q7N6PFJCUOCKDIS7TQ4YCM/action/citation_signature","submit_replication":"https://pith.science/pith/67T4Q7N6PFJCUOCKDIS7TQ4YCM/action/replication_record"}},"created_at":"2026-07-05T11:40:12.801764+00:00","updated_at":"2026-07-05T11:40:12.801764+00:00"}