{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:FMVHHN7NB5J5CLAMS7JKIGFNBF","short_pith_number":"pith:FMVHHN7N","schema_version":"1.0","canonical_sha256":"2b2a73b7ed0f53d12c0c97d2a418ad09699c9c3bd3af24fcb60ab64bd15fb7a8","source":{"kind":"arxiv","id":"2507.02929","version":1},"attestation_state":"computed","paper":{"title":"OBSER: Object-Based Sub-Environment Recognition for Zero-Shot Environmental Inference","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","stat.ML"],"primary_cat":"cs.CV","authors_text":"Byoung-Tak Zhang, Dong-Sig Han, Hyeonseo Yang, Suhyung Choi, Won-Seok Choi","submitted_at":"2025-06-26T05:57:06Z","abstract_excerpt":"We present the Object-Based Sub-Environment Recognition (OBSER) framework, a novel Bayesian framework that infers three fundamental relationships between sub-environments and their constituent objects. In the OBSER framework, metric and self-supervised learning models estimate the object distributions of sub-environments on the latent space to compute these measures. Both theoretically and empirically, we validate the proposed framework by introducing the ($\\epsilon,\\delta$) statistically separable (EDS) function which indicates the alignment of the representation. Our framework reliably perfo"},"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":"2507.02929","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-06-26T05:57:06Z","cross_cats_sorted":["cs.AI","cs.LG","stat.ML"],"title_canon_sha256":"f675a711c37d8f9ab8ca28b649347576e31887efb4977115c0e0c181c9f765c1","abstract_canon_sha256":"afbc0c6094a74c53d1f9a4eaa39072330e436fd5edbf0dff68bac135c9c87a2c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:31:48.947575Z","signature_b64":"X6WydGCQBLuSIMazF3lUc9EQ+Wiy0hCdrfSluMRfRu3SGLCHFpmQqzyvCslTlR4ZRMdt12Q0koWcZJlIXrF6Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2b2a73b7ed0f53d12c0c97d2a418ad09699c9c3bd3af24fcb60ab64bd15fb7a8","last_reissued_at":"2026-07-05T11:31:48.947092Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:31:48.947092Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"OBSER: Object-Based Sub-Environment Recognition for Zero-Shot Environmental Inference","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","stat.ML"],"primary_cat":"cs.CV","authors_text":"Byoung-Tak Zhang, Dong-Sig Han, Hyeonseo Yang, Suhyung Choi, Won-Seok Choi","submitted_at":"2025-06-26T05:57:06Z","abstract_excerpt":"We present the Object-Based Sub-Environment Recognition (OBSER) framework, a novel Bayesian framework that infers three fundamental relationships between sub-environments and their constituent objects. In the OBSER framework, metric and self-supervised learning models estimate the object distributions of sub-environments on the latent space to compute these measures. Both theoretically and empirically, we validate the proposed framework by introducing the ($\\epsilon,\\delta$) statistically separable (EDS) function which indicates the alignment of the representation. Our framework reliably perfo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.02929","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/2507.02929/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":"2507.02929","created_at":"2026-07-05T11:31:48.947147+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.02929v1","created_at":"2026-07-05T11:31:48.947147+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.02929","created_at":"2026-07-05T11:31:48.947147+00:00"},{"alias_kind":"pith_short_12","alias_value":"FMVHHN7NB5J5","created_at":"2026-07-05T11:31:48.947147+00:00"},{"alias_kind":"pith_short_16","alias_value":"FMVHHN7NB5J5CLAM","created_at":"2026-07-05T11:31:48.947147+00:00"},{"alias_kind":"pith_short_8","alias_value":"FMVHHN7N","created_at":"2026-07-05T11:31:48.947147+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/FMVHHN7NB5J5CLAMS7JKIGFNBF","json":"https://pith.science/pith/FMVHHN7NB5J5CLAMS7JKIGFNBF.json","graph_json":"https://pith.science/api/pith-number/FMVHHN7NB5J5CLAMS7JKIGFNBF/graph.json","events_json":"https://pith.science/api/pith-number/FMVHHN7NB5J5CLAMS7JKIGFNBF/events.json","paper":"https://pith.science/paper/FMVHHN7N"},"agent_actions":{"view_html":"https://pith.science/pith/FMVHHN7NB5J5CLAMS7JKIGFNBF","download_json":"https://pith.science/pith/FMVHHN7NB5J5CLAMS7JKIGFNBF.json","view_paper":"https://pith.science/paper/FMVHHN7N","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.02929&json=true","fetch_graph":"https://pith.science/api/pith-number/FMVHHN7NB5J5CLAMS7JKIGFNBF/graph.json","fetch_events":"https://pith.science/api/pith-number/FMVHHN7NB5J5CLAMS7JKIGFNBF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FMVHHN7NB5J5CLAMS7JKIGFNBF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FMVHHN7NB5J5CLAMS7JKIGFNBF/action/storage_attestation","attest_author":"https://pith.science/pith/FMVHHN7NB5J5CLAMS7JKIGFNBF/action/author_attestation","sign_citation":"https://pith.science/pith/FMVHHN7NB5J5CLAMS7JKIGFNBF/action/citation_signature","submit_replication":"https://pith.science/pith/FMVHHN7NB5J5CLAMS7JKIGFNBF/action/replication_record"}},"created_at":"2026-07-05T11:31:48.947147+00:00","updated_at":"2026-07-05T11:31:48.947147+00:00"}