{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:A5YAIT6FPYXXWYKAP4V6WZUTCO","short_pith_number":"pith:A5YAIT6F","schema_version":"1.0","canonical_sha256":"0770044fc57e2f7b61407f2beb669313a0968f6a2a1bc94c2088b5bfdeb6a93c","source":{"kind":"arxiv","id":"2607.06217","version":1},"attestation_state":"computed","paper":{"title":"EeveeDark: A Binary Neural Framework for Low-Light Video Enhancement via Event-Guided Sensor-Level Fusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aykut Erdem, Erkut Erdem, Onur Eker","submitted_at":"2026-07-07T12:41:36Z","abstract_excerpt":"Enhancing videos under extreme low-light conditions remains challenging due to the difficulty of balancing restoration quality and computational efficiency in resource-constrained settings. This paper introduces EeveeDark, a low-light video enhancement framework that combines the spatial richness of sensor-level RAW data with the temporal precision of event streams. Central to our model is a Binary Neural Network (BNN) architecture that reduces computational overhead by quantizing weights and activations while preserving detail. EeveeDark incorporates (i) modality-specific binary encoders for "},"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":"2607.06217","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-07-07T12:41:36Z","cross_cats_sorted":[],"title_canon_sha256":"0cd9dde45d1a0bb3044630e79850fef03c5eed7ed39afc538333b1426a8ac16b","abstract_canon_sha256":"9d586350dc3b189fbd0e7e4fec9eed569be8d4293d92694d20c222301677b32d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-08T01:19:18.127989Z","signature_b64":"Mqzk0rG5vWHsE+2ouqOTCnna8EINY6Z1V2b3z1kLTDSAqq5RfIOyMp5Xlr+gRIafBlC4Q6VTbr2kFtjRMKW0DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0770044fc57e2f7b61407f2beb669313a0968f6a2a1bc94c2088b5bfdeb6a93c","last_reissued_at":"2026-07-08T01:19:18.127566Z","signature_status":"signed_v1","first_computed_at":"2026-07-08T01:19:18.127566Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"EeveeDark: A Binary Neural Framework for Low-Light Video Enhancement via Event-Guided Sensor-Level Fusion","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Aykut Erdem, Erkut Erdem, Onur Eker","submitted_at":"2026-07-07T12:41:36Z","abstract_excerpt":"Enhancing videos under extreme low-light conditions remains challenging due to the difficulty of balancing restoration quality and computational efficiency in resource-constrained settings. This paper introduces EeveeDark, a low-light video enhancement framework that combines the spatial richness of sensor-level RAW data with the temporal precision of event streams. Central to our model is a Binary Neural Network (BNN) architecture that reduces computational overhead by quantizing weights and activations while preserving detail. EeveeDark incorporates (i) modality-specific binary encoders for "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.06217","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/2607.06217/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":"2607.06217","created_at":"2026-07-08T01:19:18.127623+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.06217v1","created_at":"2026-07-08T01:19:18.127623+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.06217","created_at":"2026-07-08T01:19:18.127623+00:00"},{"alias_kind":"pith_short_12","alias_value":"A5YAIT6FPYXX","created_at":"2026-07-08T01:19:18.127623+00:00"},{"alias_kind":"pith_short_16","alias_value":"A5YAIT6FPYXXWYKA","created_at":"2026-07-08T01:19:18.127623+00:00"},{"alias_kind":"pith_short_8","alias_value":"A5YAIT6F","created_at":"2026-07-08T01:19:18.127623+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/A5YAIT6FPYXXWYKAP4V6WZUTCO","json":"https://pith.science/pith/A5YAIT6FPYXXWYKAP4V6WZUTCO.json","graph_json":"https://pith.science/api/pith-number/A5YAIT6FPYXXWYKAP4V6WZUTCO/graph.json","events_json":"https://pith.science/api/pith-number/A5YAIT6FPYXXWYKAP4V6WZUTCO/events.json","paper":"https://pith.science/paper/A5YAIT6F"},"agent_actions":{"view_html":"https://pith.science/pith/A5YAIT6FPYXXWYKAP4V6WZUTCO","download_json":"https://pith.science/pith/A5YAIT6FPYXXWYKAP4V6WZUTCO.json","view_paper":"https://pith.science/paper/A5YAIT6F","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.06217&json=true","fetch_graph":"https://pith.science/api/pith-number/A5YAIT6FPYXXWYKAP4V6WZUTCO/graph.json","fetch_events":"https://pith.science/api/pith-number/A5YAIT6FPYXXWYKAP4V6WZUTCO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A5YAIT6FPYXXWYKAP4V6WZUTCO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A5YAIT6FPYXXWYKAP4V6WZUTCO/action/storage_attestation","attest_author":"https://pith.science/pith/A5YAIT6FPYXXWYKAP4V6WZUTCO/action/author_attestation","sign_citation":"https://pith.science/pith/A5YAIT6FPYXXWYKAP4V6WZUTCO/action/citation_signature","submit_replication":"https://pith.science/pith/A5YAIT6FPYXXWYKAP4V6WZUTCO/action/replication_record"}},"created_at":"2026-07-08T01:19:18.127623+00:00","updated_at":"2026-07-08T01:19:18.127623+00:00"}