{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:WS6NVQEY5G4DSVEKKVC3EAGOLE","short_pith_number":"pith:WS6NVQEY","schema_version":"1.0","canonical_sha256":"b4bcdac098e9b839548a5545b200ce59398957b273b308404127e40b3f86679e","source":{"kind":"arxiv","id":"2308.02126","version":2},"attestation_state":"computed","paper":{"title":"Cognitive TransFuser: Semantics-guided Transformer-based Sensor Fusion for Improved Waypoint Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Hwan-Soo Choi, Jong-Hwan Kim, Jongoh Jeong, Kuk-Jin Yoon, Young Hoo Cho","submitted_at":"2023-08-04T03:59:10Z","abstract_excerpt":"Sensor fusion approaches for intelligent self-driving agents remain key to driving scene understanding given visual global contexts acquired from input sensors. Specifically, for the local waypoint prediction task, single-modality networks are still limited by strong dependency on the sensitivity of the input sensor, and thus recent works therefore promote the use of multiple sensors in fusion in feature level in practice. While it is well known that multiple data modalities encourage mutual contextual exchange, it requires global 3D scene understanding in real-time with minimal computation up"},"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":"2308.02126","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-08-04T03:59:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2980673f324359c5c0198ec1ca410bdbf25b733e505099e547498c97dda712e6","abstract_canon_sha256":"d0bbd2de87df1a439fe3058c7247ed1fd009750567ded4fefe9bec15b4288948"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:39:29.123268Z","signature_b64":"M7ohi6YCssPqPsZ+PfCuNKOLwKPtqa+lw4lRE3hsPwIJoqvoPeXcv2z8XBkGrTrhr4nj8LZ+MWfncLzDkiRHAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b4bcdac098e9b839548a5545b200ce59398957b273b308404127e40b3f86679e","last_reissued_at":"2026-07-05T07:39:29.122802Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:39:29.122802Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Cognitive TransFuser: Semantics-guided Transformer-based Sensor Fusion for Improved Waypoint Prediction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Hwan-Soo Choi, Jong-Hwan Kim, Jongoh Jeong, Kuk-Jin Yoon, Young Hoo Cho","submitted_at":"2023-08-04T03:59:10Z","abstract_excerpt":"Sensor fusion approaches for intelligent self-driving agents remain key to driving scene understanding given visual global contexts acquired from input sensors. Specifically, for the local waypoint prediction task, single-modality networks are still limited by strong dependency on the sensitivity of the input sensor, and thus recent works therefore promote the use of multiple sensors in fusion in feature level in practice. While it is well known that multiple data modalities encourage mutual contextual exchange, it requires global 3D scene understanding in real-time with minimal computation up"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.02126","kind":"arxiv","version":2},"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/2308.02126/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":"2308.02126","created_at":"2026-07-05T07:39:29.122860+00:00"},{"alias_kind":"arxiv_version","alias_value":"2308.02126v2","created_at":"2026-07-05T07:39:29.122860+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.02126","created_at":"2026-07-05T07:39:29.122860+00:00"},{"alias_kind":"pith_short_12","alias_value":"WS6NVQEY5G4D","created_at":"2026-07-05T07:39:29.122860+00:00"},{"alias_kind":"pith_short_16","alias_value":"WS6NVQEY5G4DSVEK","created_at":"2026-07-05T07:39:29.122860+00:00"},{"alias_kind":"pith_short_8","alias_value":"WS6NVQEY","created_at":"2026-07-05T07:39:29.122860+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/WS6NVQEY5G4DSVEKKVC3EAGOLE","json":"https://pith.science/pith/WS6NVQEY5G4DSVEKKVC3EAGOLE.json","graph_json":"https://pith.science/api/pith-number/WS6NVQEY5G4DSVEKKVC3EAGOLE/graph.json","events_json":"https://pith.science/api/pith-number/WS6NVQEY5G4DSVEKKVC3EAGOLE/events.json","paper":"https://pith.science/paper/WS6NVQEY"},"agent_actions":{"view_html":"https://pith.science/pith/WS6NVQEY5G4DSVEKKVC3EAGOLE","download_json":"https://pith.science/pith/WS6NVQEY5G4DSVEKKVC3EAGOLE.json","view_paper":"https://pith.science/paper/WS6NVQEY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2308.02126&json=true","fetch_graph":"https://pith.science/api/pith-number/WS6NVQEY5G4DSVEKKVC3EAGOLE/graph.json","fetch_events":"https://pith.science/api/pith-number/WS6NVQEY5G4DSVEKKVC3EAGOLE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WS6NVQEY5G4DSVEKKVC3EAGOLE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WS6NVQEY5G4DSVEKKVC3EAGOLE/action/storage_attestation","attest_author":"https://pith.science/pith/WS6NVQEY5G4DSVEKKVC3EAGOLE/action/author_attestation","sign_citation":"https://pith.science/pith/WS6NVQEY5G4DSVEKKVC3EAGOLE/action/citation_signature","submit_replication":"https://pith.science/pith/WS6NVQEY5G4DSVEKKVC3EAGOLE/action/replication_record"}},"created_at":"2026-07-05T07:39:29.122860+00:00","updated_at":"2026-07-05T07:39:29.122860+00:00"}