{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:75AQMV7U24EJLILAZFDIEYSTIM","short_pith_number":"pith:75AQMV7U","schema_version":"1.0","canonical_sha256":"ff410657f4d70895a160c9468262534331409d853c921081ff5fbb7d07809a03","source":{"kind":"arxiv","id":"2606.06447","version":1},"attestation_state":"computed","paper":{"title":"Latent Reasoning with Normalizing Flows","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Guancheng Tu, Haoqiang Kang, Jiatao Gu, Lianhui Qin, Suhao Yu, Xiangjun Fu, Yao Tang, Yizhe Zhang","submitted_at":"2026-06-04T17:44:17Z","abstract_excerpt":"Large language models often improve reasoning by generating explicit chain-of-thought (CoT), demonstrating the importance of intermediate computation. However, textual CoT forces this computation through a discrete, serial, and communication-oriented token stream: each reasoning step must be verbalized before the model can proceed, even when the underlying update is semantic, uncertain, or only partially formed. Latent reasoning offers a higher-bandwidth alternative by performing intermediate computation in compact continuous states before committing to text. Yet existing latent-reasoning meth"},"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":"2606.06447","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-06-04T17:44:17Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6a4a93a717ee6ce44b3a5a89a700afa17f4cae1efe91c2721be495e896dcde58","abstract_canon_sha256":"1395003b51227d03785863e1fd273060a3509ff5f9b5225b8e1acfa709304ed8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T01:15:45.826288Z","signature_b64":"NGQvPxGq0VZ4MOyZqGjlWAna7igmIY8KE0vmjTmE9SnlX+83xzIKJ05fMunGoU2NBOtAmHVRBuoQHyz8BSDSDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ff410657f4d70895a160c9468262534331409d853c921081ff5fbb7d07809a03","last_reissued_at":"2026-06-05T01:15:45.825738Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T01:15:45.825738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Latent Reasoning with Normalizing Flows","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Guancheng Tu, Haoqiang Kang, Jiatao Gu, Lianhui Qin, Suhao Yu, Xiangjun Fu, Yao Tang, Yizhe Zhang","submitted_at":"2026-06-04T17:44:17Z","abstract_excerpt":"Large language models often improve reasoning by generating explicit chain-of-thought (CoT), demonstrating the importance of intermediate computation. However, textual CoT forces this computation through a discrete, serial, and communication-oriented token stream: each reasoning step must be verbalized before the model can proceed, even when the underlying update is semantic, uncertain, or only partially formed. Latent reasoning offers a higher-bandwidth alternative by performing intermediate computation in compact continuous states before committing to text. Yet existing latent-reasoning meth"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.06447","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/2606.06447/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":"2606.06447","created_at":"2026-06-05T01:15:45.825796+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.06447v1","created_at":"2026-06-05T01:15:45.825796+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.06447","created_at":"2026-06-05T01:15:45.825796+00:00"},{"alias_kind":"pith_short_12","alias_value":"75AQMV7U24EJ","created_at":"2026-06-05T01:15:45.825796+00:00"},{"alias_kind":"pith_short_16","alias_value":"75AQMV7U24EJLILA","created_at":"2026-06-05T01:15:45.825796+00:00"},{"alias_kind":"pith_short_8","alias_value":"75AQMV7U","created_at":"2026-06-05T01:15:45.825796+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/75AQMV7U24EJLILAZFDIEYSTIM","json":"https://pith.science/pith/75AQMV7U24EJLILAZFDIEYSTIM.json","graph_json":"https://pith.science/api/pith-number/75AQMV7U24EJLILAZFDIEYSTIM/graph.json","events_json":"https://pith.science/api/pith-number/75AQMV7U24EJLILAZFDIEYSTIM/events.json","paper":"https://pith.science/paper/75AQMV7U"},"agent_actions":{"view_html":"https://pith.science/pith/75AQMV7U24EJLILAZFDIEYSTIM","download_json":"https://pith.science/pith/75AQMV7U24EJLILAZFDIEYSTIM.json","view_paper":"https://pith.science/paper/75AQMV7U","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.06447&json=true","fetch_graph":"https://pith.science/api/pith-number/75AQMV7U24EJLILAZFDIEYSTIM/graph.json","fetch_events":"https://pith.science/api/pith-number/75AQMV7U24EJLILAZFDIEYSTIM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/75AQMV7U24EJLILAZFDIEYSTIM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/75AQMV7U24EJLILAZFDIEYSTIM/action/storage_attestation","attest_author":"https://pith.science/pith/75AQMV7U24EJLILAZFDIEYSTIM/action/author_attestation","sign_citation":"https://pith.science/pith/75AQMV7U24EJLILAZFDIEYSTIM/action/citation_signature","submit_replication":"https://pith.science/pith/75AQMV7U24EJLILAZFDIEYSTIM/action/replication_record"}},"created_at":"2026-06-05T01:15:45.825796+00:00","updated_at":"2026-06-05T01:15:45.825796+00:00"}