{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:SNOGBQ6DZNQJKHKWL5KKCFEGU2","short_pith_number":"pith:SNOGBQ6D","canonical_record":{"source":{"id":"2210.09636","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-18T07:10:38Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"b7a327adcd160ad4cdf6f95261cae78e2d496471111c8a52c03402d66c4e5c38","abstract_canon_sha256":"325dd37ab5e0ebef2e4be130636c1c17c125526e671dfc94234b448416d7054d"},"schema_version":"1.0"},"canonical_sha256":"935c60c3c3cb60951d565f54a11486a692a1bc004944d1251300ad922917d9ac","source":{"kind":"arxiv","id":"2210.09636","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.09636","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"arxiv_version","alias_value":"2210.09636v1","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.09636","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"pith_short_12","alias_value":"SNOGBQ6DZNQJ","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"pith_short_16","alias_value":"SNOGBQ6DZNQJKHKW","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"pith_short_8","alias_value":"SNOGBQ6D","created_at":"2026-07-05T05:07:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:SNOGBQ6DZNQJKHKWL5KKCFEGU2","target":"record","payload":{"canonical_record":{"source":{"id":"2210.09636","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-18T07:10:38Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"b7a327adcd160ad4cdf6f95261cae78e2d496471111c8a52c03402d66c4e5c38","abstract_canon_sha256":"325dd37ab5e0ebef2e4be130636c1c17c125526e671dfc94234b448416d7054d"},"schema_version":"1.0"},"canonical_sha256":"935c60c3c3cb60951d565f54a11486a692a1bc004944d1251300ad922917d9ac","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:07:57.761009Z","signature_b64":"7YetiU1DazFo4pof/uxAAAgiYaUQnHeYFZsUmwCCrtQG/OULxOzSRIZmIYyNpP2dGNQVzonAVJkeLPY+DqUlAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"935c60c3c3cb60951d565f54a11486a692a1bc004944d1251300ad922917d9ac","last_reissued_at":"2026-07-05T05:07:57.760622Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:07:57.760622Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.09636","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:07:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"839zGvGIh3dM1StwUYUFo7OFcZac+GI6ClsLp7AdOJ3EKXzcybfPINa9Fhr91H7lWAiWXh+ragrt4YajQNReAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T23:11:16.693171Z"},"content_sha256":"af34de0caff3858f7a24f40192ecc70ed5d7c41d70a99960eace6b9c63d767af","schema_version":"1.0","event_id":"sha256:af34de0caff3858f7a24f40192ecc70ed5d7c41d70a99960eace6b9c63d767af"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:SNOGBQ6DZNQJKHKWL5KKCFEGU2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Split-KalmanNet: A Robust Model-Based Deep Learning Approach for SLAM","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.RO"],"primary_cat":"eess.SP","authors_text":"Geon Choi, Jeonghun Park, Namyoon Lee, Nir Shlezinger, Yonina C. Eldar","submitted_at":"2022-10-18T07:10:38Z","abstract_excerpt":"Simultaneous localization and mapping (SLAM) is a method that constructs a map of an unknown environment and localizes the position of a moving agent on the map simultaneously. Extended Kalman filter (EKF) has been widely adopted as a low complexity solution for online SLAM, which relies on a motion and measurement model of the moving agent. In practice, however, acquiring precise information about these models is very challenging, and the model mismatch effect causes severe performance loss in SLAM. In this paper, inspired by the recently proposed KalmanNet, we present a robust EKF algorithm "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.09636","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/2210.09636/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:07:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rDscFDhmkCnVJ2SZKLyHrRU3VtTvETbOawneq5nPUfRvxBA9uBwQdKxMwSS4QHXir0g5igO0xM1LwaVIL+aGDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T23:11:16.693740Z"},"content_sha256":"588c545572e7ed15e05ff7088d608be9b638f7ddfd23a065e372290350f36566","schema_version":"1.0","event_id":"sha256:588c545572e7ed15e05ff7088d608be9b638f7ddfd23a065e372290350f36566"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SNOGBQ6DZNQJKHKWL5KKCFEGU2/bundle.json","state_url":"https://pith.science/pith/SNOGBQ6DZNQJKHKWL5KKCFEGU2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SNOGBQ6DZNQJKHKWL5KKCFEGU2/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-20T23:11:16Z","links":{"resolver":"https://pith.science/pith/SNOGBQ6DZNQJKHKWL5KKCFEGU2","bundle":"https://pith.science/pith/SNOGBQ6DZNQJKHKWL5KKCFEGU2/bundle.json","state":"https://pith.science/pith/SNOGBQ6DZNQJKHKWL5KKCFEGU2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SNOGBQ6DZNQJKHKWL5KKCFEGU2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:SNOGBQ6DZNQJKHKWL5KKCFEGU2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"325dd37ab5e0ebef2e4be130636c1c17c125526e671dfc94234b448416d7054d","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-18T07:10:38Z","title_canon_sha256":"b7a327adcd160ad4cdf6f95261cae78e2d496471111c8a52c03402d66c4e5c38"},"schema_version":"1.0","source":{"id":"2210.09636","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.09636","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"arxiv_version","alias_value":"2210.09636v1","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.09636","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"pith_short_12","alias_value":"SNOGBQ6DZNQJ","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"pith_short_16","alias_value":"SNOGBQ6DZNQJKHKW","created_at":"2026-07-05T05:07:57Z"},{"alias_kind":"pith_short_8","alias_value":"SNOGBQ6D","created_at":"2026-07-05T05:07:57Z"}],"graph_snapshots":[{"event_id":"sha256:588c545572e7ed15e05ff7088d608be9b638f7ddfd23a065e372290350f36566","target":"graph","created_at":"2026-07-05T05:07:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2210.09636/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Simultaneous localization and mapping (SLAM) is a method that constructs a map of an unknown environment and localizes the position of a moving agent on the map simultaneously. Extended Kalman filter (EKF) has been widely adopted as a low complexity solution for online SLAM, which relies on a motion and measurement model of the moving agent. In practice, however, acquiring precise information about these models is very challenging, and the model mismatch effect causes severe performance loss in SLAM. In this paper, inspired by the recently proposed KalmanNet, we present a robust EKF algorithm ","authors_text":"Geon Choi, Jeonghun Park, Namyoon Lee, Nir Shlezinger, Yonina C. Eldar","cross_cats":["cs.LG","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-18T07:10:38Z","title":"Split-KalmanNet: A Robust Model-Based Deep Learning Approach for SLAM"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.09636","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:af34de0caff3858f7a24f40192ecc70ed5d7c41d70a99960eace6b9c63d767af","target":"record","created_at":"2026-07-05T05:07:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"325dd37ab5e0ebef2e4be130636c1c17c125526e671dfc94234b448416d7054d","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2022-10-18T07:10:38Z","title_canon_sha256":"b7a327adcd160ad4cdf6f95261cae78e2d496471111c8a52c03402d66c4e5c38"},"schema_version":"1.0","source":{"id":"2210.09636","kind":"arxiv","version":1}},"canonical_sha256":"935c60c3c3cb60951d565f54a11486a692a1bc004944d1251300ad922917d9ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"935c60c3c3cb60951d565f54a11486a692a1bc004944d1251300ad922917d9ac","first_computed_at":"2026-07-05T05:07:57.760622Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:07:57.760622Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7YetiU1DazFo4pof/uxAAAgiYaUQnHeYFZsUmwCCrtQG/OULxOzSRIZmIYyNpP2dGNQVzonAVJkeLPY+DqUlAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:07:57.761009Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.09636","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:af34de0caff3858f7a24f40192ecc70ed5d7c41d70a99960eace6b9c63d767af","sha256:588c545572e7ed15e05ff7088d608be9b638f7ddfd23a065e372290350f36566"],"state_sha256":"a0a756c13007c584ead20f6cb746ce44de58a3254809701c3ab024da1a72121e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aFGiyBrviAK98MZdswSHcXH02i963aagIRH7p+/xn7KACd8V+CiKQYiVY/35ZfoGbEAyUAlkDbJQd0jd5DO6BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T23:11:16.698638Z","bundle_sha256":"971662bb80b554ddfab4e0ee94b481c93dcba0066e23c8ba6cf35b630482e4e4"}}