{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:E7EL555HES7PGJGDGT4XPGV43F","short_pith_number":"pith:E7EL555H","schema_version":"1.0","canonical_sha256":"27c8bef7a724bef324c334f9779abcd96bc9d6130bc99da368c686c50924392a","source":{"kind":"arxiv","id":"2605.29773","version":1},"attestation_state":"computed","paper":{"title":"Energy-Aware NECO for Single-Pass Pixel-wise Out-of-Distribution Detection in Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.RO"],"primary_cat":"cs.CV","authors_text":"Boyuan Zhang, Huanshan Huang, Yifei Cao","submitted_at":"2026-05-28T11:19:46Z","abstract_excerpt":"Reliable semantic segmentation for mobile robots requires both accurate dense prediction and robust uncertainty estimation under distribution shift. Strong uncertainty baselines such as Monte Carlo Dropout often require repeated stochastic forward passes and are difficult to deploy on edge platforms.\n  We propose Energy-Aware NECO, a single-pass pixel-wise out-of-distribution (OOD) detector for semantic segmentation. The method combines a centered NECO-style geometric ratio computed from decoder features with a logit-based Energy score. Both components are standardized using statistics fitted "},"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":"2605.29773","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T11:19:46Z","cross_cats_sorted":["cs.AI","cs.RO"],"title_canon_sha256":"8c070c895f88343112c8a720ad33ae2d7ae43c530a38b08b75e89bc63185e5a0","abstract_canon_sha256":"ab36bfb867f21307307eb6435e34ad0c1058327709587ed5991168cf5becb672"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T02:05:25.756407Z","signature_b64":"wE23BOqz387xIZYR90JE1aNYMUPS4ThMua2WirywkEEPwIrJdnc1o/51VE1fmSukNQjDYOHc2gYsaLdAsfBgDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"27c8bef7a724bef324c334f9779abcd96bc9d6130bc99da368c686c50924392a","last_reissued_at":"2026-05-29T02:05:25.755947Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T02:05:25.755947Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Energy-Aware NECO for Single-Pass Pixel-wise Out-of-Distribution Detection in Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.RO"],"primary_cat":"cs.CV","authors_text":"Boyuan Zhang, Huanshan Huang, Yifei Cao","submitted_at":"2026-05-28T11:19:46Z","abstract_excerpt":"Reliable semantic segmentation for mobile robots requires both accurate dense prediction and robust uncertainty estimation under distribution shift. Strong uncertainty baselines such as Monte Carlo Dropout often require repeated stochastic forward passes and are difficult to deploy on edge platforms.\n  We propose Energy-Aware NECO, a single-pass pixel-wise out-of-distribution (OOD) detector for semantic segmentation. The method combines a centered NECO-style geometric ratio computed from decoder features with a logit-based Energy score. Both components are standardized using statistics fitted "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29773","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/2605.29773/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":"2605.29773","created_at":"2026-05-29T02:05:25.756004+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.29773v1","created_at":"2026-05-29T02:05:25.756004+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29773","created_at":"2026-05-29T02:05:25.756004+00:00"},{"alias_kind":"pith_short_12","alias_value":"E7EL555HES7P","created_at":"2026-05-29T02:05:25.756004+00:00"},{"alias_kind":"pith_short_16","alias_value":"E7EL555HES7PGJGD","created_at":"2026-05-29T02:05:25.756004+00:00"},{"alias_kind":"pith_short_8","alias_value":"E7EL555H","created_at":"2026-05-29T02:05:25.756004+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/E7EL555HES7PGJGDGT4XPGV43F","json":"https://pith.science/pith/E7EL555HES7PGJGDGT4XPGV43F.json","graph_json":"https://pith.science/api/pith-number/E7EL555HES7PGJGDGT4XPGV43F/graph.json","events_json":"https://pith.science/api/pith-number/E7EL555HES7PGJGDGT4XPGV43F/events.json","paper":"https://pith.science/paper/E7EL555H"},"agent_actions":{"view_html":"https://pith.science/pith/E7EL555HES7PGJGDGT4XPGV43F","download_json":"https://pith.science/pith/E7EL555HES7PGJGDGT4XPGV43F.json","view_paper":"https://pith.science/paper/E7EL555H","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.29773&json=true","fetch_graph":"https://pith.science/api/pith-number/E7EL555HES7PGJGDGT4XPGV43F/graph.json","fetch_events":"https://pith.science/api/pith-number/E7EL555HES7PGJGDGT4XPGV43F/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/E7EL555HES7PGJGDGT4XPGV43F/action/timestamp_anchor","attest_storage":"https://pith.science/pith/E7EL555HES7PGJGDGT4XPGV43F/action/storage_attestation","attest_author":"https://pith.science/pith/E7EL555HES7PGJGDGT4XPGV43F/action/author_attestation","sign_citation":"https://pith.science/pith/E7EL555HES7PGJGDGT4XPGV43F/action/citation_signature","submit_replication":"https://pith.science/pith/E7EL555HES7PGJGDGT4XPGV43F/action/replication_record"}},"created_at":"2026-05-29T02:05:25.756004+00:00","updated_at":"2026-05-29T02:05:25.756004+00:00"}