{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:V2DHTKHTLFPH5SYFHO2BOFJJWH","short_pith_number":"pith:V2DHTKHT","schema_version":"1.0","canonical_sha256":"ae8679a8f3595e7ecb053bb4171529b1c51a4cc0b83a9e70a05d9230ec251880","source":{"kind":"arxiv","id":"2606.18687","version":1},"attestation_state":"computed","paper":{"title":"Spatially Stratified Distillation for Heterogeneous Radar Place Recognition","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Abdelwahed Khamis, Peyman Moghadam, Sagun Singh Shrestha, Saimunur Rahman, Samuel Harding","submitted_at":"2026-06-17T04:55:42Z","abstract_excerpt":"Scalable, all-weather place recognition increasingly relies on heterogeneous radar place recognition to bridge diverse hardware platforms. A notable application is matching queries from cost-effective 4D automotive radars against high-fidelity reference maps built by dense spinning radars. This process is fundamentally limited by the extreme sparsity (and narrow field-of-view) of the 4D sensor, which captures only a fraction of the structural density present in the spinning radar database. Prior efforts address this issue by unifying different radar signals. That is, projecting both signals in"},"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":"2606.18687","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-17T04:55:42Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"85b0e6a0c7f463912bba7eaae133ef561fb485d1862cf58601d0d907dfd3e43e","abstract_canon_sha256":"96bccf96bd20020e2824e5c8e9ba28e89f87ce6ec7aa345d337fb907803cc124"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:11:44.568274Z","signature_b64":"Tb8dhTdXcHRVnkqZbv18dGWoH6Rpem5ZjxKxxaV1zSsr4UOndnDALJYjZYfPM47uyKwcVlF5Bmb8G0cuIpSnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae8679a8f3595e7ecb053bb4171529b1c51a4cc0b83a9e70a05d9230ec251880","last_reissued_at":"2026-06-19T16:11:44.567931Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:11:44.567931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Spatially Stratified Distillation for Heterogeneous Radar Place Recognition","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.CV","authors_text":"Abdelwahed Khamis, Peyman Moghadam, Sagun Singh Shrestha, Saimunur Rahman, Samuel Harding","submitted_at":"2026-06-17T04:55:42Z","abstract_excerpt":"Scalable, all-weather place recognition increasingly relies on heterogeneous radar place recognition to bridge diverse hardware platforms. A notable application is matching queries from cost-effective 4D automotive radars against high-fidelity reference maps built by dense spinning radars. This process is fundamentally limited by the extreme sparsity (and narrow field-of-view) of the 4D sensor, which captures only a fraction of the structural density present in the spinning radar database. Prior efforts address this issue by unifying different radar signals. That is, projecting both signals in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.18687","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/2606.18687/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":"2606.18687","created_at":"2026-06-19T16:11:44.567992+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.18687v1","created_at":"2026-06-19T16:11:44.567992+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.18687","created_at":"2026-06-19T16:11:44.567992+00:00"},{"alias_kind":"pith_short_12","alias_value":"V2DHTKHTLFPH","created_at":"2026-06-19T16:11:44.567992+00:00"},{"alias_kind":"pith_short_16","alias_value":"V2DHTKHTLFPH5SYF","created_at":"2026-06-19T16:11:44.567992+00:00"},{"alias_kind":"pith_short_8","alias_value":"V2DHTKHT","created_at":"2026-06-19T16:11:44.567992+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/V2DHTKHTLFPH5SYFHO2BOFJJWH","json":"https://pith.science/pith/V2DHTKHTLFPH5SYFHO2BOFJJWH.json","graph_json":"https://pith.science/api/pith-number/V2DHTKHTLFPH5SYFHO2BOFJJWH/graph.json","events_json":"https://pith.science/api/pith-number/V2DHTKHTLFPH5SYFHO2BOFJJWH/events.json","paper":"https://pith.science/paper/V2DHTKHT"},"agent_actions":{"view_html":"https://pith.science/pith/V2DHTKHTLFPH5SYFHO2BOFJJWH","download_json":"https://pith.science/pith/V2DHTKHTLFPH5SYFHO2BOFJJWH.json","view_paper":"https://pith.science/paper/V2DHTKHT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.18687&json=true","fetch_graph":"https://pith.science/api/pith-number/V2DHTKHTLFPH5SYFHO2BOFJJWH/graph.json","fetch_events":"https://pith.science/api/pith-number/V2DHTKHTLFPH5SYFHO2BOFJJWH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/V2DHTKHTLFPH5SYFHO2BOFJJWH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/V2DHTKHTLFPH5SYFHO2BOFJJWH/action/storage_attestation","attest_author":"https://pith.science/pith/V2DHTKHTLFPH5SYFHO2BOFJJWH/action/author_attestation","sign_citation":"https://pith.science/pith/V2DHTKHTLFPH5SYFHO2BOFJJWH/action/citation_signature","submit_replication":"https://pith.science/pith/V2DHTKHTLFPH5SYFHO2BOFJJWH/action/replication_record"}},"created_at":"2026-06-19T16:11:44.567992+00:00","updated_at":"2026-06-19T16:11:44.567992+00:00"}