{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:5YOMJEIOBEOXBLQ7WQBDYVIHQG","short_pith_number":"pith:5YOMJEIO","canonical_record":{"source":{"id":"2607.20521","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-09T00:05:23Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"2204796cef84fa5708f15c1b82c1b330cf8e6bb012aa8119a92c432e7dca501d","abstract_canon_sha256":"3c63a28d54527c7e976cc95d7d5e995285bc2649489b57ad6cef2391662ec953"},"schema_version":"1.0"},"canonical_sha256":"ee1cc4910e091d70ae1fb4023c550781958db9318ba49d48f1d0ed905db800c6","source":{"kind":"arxiv","id":"2607.20521","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.20521","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"arxiv_version","alias_value":"2607.20521v1","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.20521","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"pith_short_12","alias_value":"5YOMJEIOBEOX","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"pith_short_16","alias_value":"5YOMJEIOBEOXBLQ7","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"pith_short_8","alias_value":"5YOMJEIO","created_at":"2026-07-24T00:23:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:5YOMJEIOBEOXBLQ7WQBDYVIHQG","target":"record","payload":{"canonical_record":{"source":{"id":"2607.20521","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-09T00:05:23Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"2204796cef84fa5708f15c1b82c1b330cf8e6bb012aa8119a92c432e7dca501d","abstract_canon_sha256":"3c63a28d54527c7e976cc95d7d5e995285bc2649489b57ad6cef2391662ec953"},"schema_version":"1.0"},"canonical_sha256":"ee1cc4910e091d70ae1fb4023c550781958db9318ba49d48f1d0ed905db800c6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-24T00:23:20.243739Z","signature_b64":"N8p31EyHiaBgSL067cJ366s99wHeefw1pSlN9ym2bLE7gBJgVqBK5mGuSuQGPy1ssZOb+ow+330WWUGeVxSIDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee1cc4910e091d70ae1fb4023c550781958db9318ba49d48f1d0ed905db800c6","last_reissued_at":"2026-07-24T00:23:20.242843Z","signature_status":"signed_v1","first_computed_at":"2026-07-24T00:23:20.242843Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.20521","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":"2026-07-24T00:23:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qeNWZ0tds0N9jLwJoyLbkOkkwdKsxgC7EsvfXWByGvnsChlU+m4ndmrBsdoqzekiEiUiBZXizJiyc2JUcwUgBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T13:01:26.289896Z"},"content_sha256":"b98832dcc11401822939000e512233ad7702429ede079e3619367668af2f7acd","schema_version":"1.0","event_id":"sha256:b98832dcc11401822939000e512233ad7702429ede079e3619367668af2f7acd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:5YOMJEIOBEOXBLQ7WQBDYVIHQG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generative Bayesian Filtering for State Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Jixin Yan, Lei Cao, Naichen Shi, Sihang Feng, Tao Sun","submitted_at":"2026-07-09T00:05:23Z","abstract_excerpt":"The state of a dynamic system evolves over time, switching among several latent modes that govern its observable behavior. Filtering methods infer the latent state from observations. Classical filtering approaches, including Kalman filters, typically rely on simple observation models, such as linear-Gaussian models, that are incapable of characterizing the increasingly nonlinear and heterogeneous patterns in high-dimensional sensor signals. To tackle the challenge, we propose Generative Bayesian Filtering (GBF), a filtering framework that replaces restrictive observation models with pretrained"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.20521","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/2607.20521/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":"2026-07-24T00:23:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ffVKaPbtYDoGNt0XMui8/Wy6VnFF88w5PjI/D6KHDBOEQ0d8vvXvRS88uhZEOXT2+sfxYF474lPSlsH0HCI+AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T13:01:26.290547Z"},"content_sha256":"03d6a1ad420ed23af72b99679a94371caa934c0cc43a896f0e3ffa52918e6d40","schema_version":"1.0","event_id":"sha256:03d6a1ad420ed23af72b99679a94371caa934c0cc43a896f0e3ffa52918e6d40"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5YOMJEIOBEOXBLQ7WQBDYVIHQG/bundle.json","state_url":"https://pith.science/pith/5YOMJEIOBEOXBLQ7WQBDYVIHQG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5YOMJEIOBEOXBLQ7WQBDYVIHQG/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":"2026-08-10T13:01:26Z","links":{"resolver":"https://pith.science/pith/5YOMJEIOBEOXBLQ7WQBDYVIHQG","bundle":"https://pith.science/pith/5YOMJEIOBEOXBLQ7WQBDYVIHQG/bundle.json","state":"https://pith.science/pith/5YOMJEIOBEOXBLQ7WQBDYVIHQG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5YOMJEIOBEOXBLQ7WQBDYVIHQG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:5YOMJEIOBEOXBLQ7WQBDYVIHQG","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":"3c63a28d54527c7e976cc95d7d5e995285bc2649489b57ad6cef2391662ec953","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-09T00:05:23Z","title_canon_sha256":"2204796cef84fa5708f15c1b82c1b330cf8e6bb012aa8119a92c432e7dca501d"},"schema_version":"1.0","source":{"id":"2607.20521","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.20521","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"arxiv_version","alias_value":"2607.20521v1","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.20521","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"pith_short_12","alias_value":"5YOMJEIOBEOX","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"pith_short_16","alias_value":"5YOMJEIOBEOXBLQ7","created_at":"2026-07-24T00:23:20Z"},{"alias_kind":"pith_short_8","alias_value":"5YOMJEIO","created_at":"2026-07-24T00:23:20Z"}],"graph_snapshots":[{"event_id":"sha256:03d6a1ad420ed23af72b99679a94371caa934c0cc43a896f0e3ffa52918e6d40","target":"graph","created_at":"2026-07-24T00:23:20Z","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/2607.20521/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The state of a dynamic system evolves over time, switching among several latent modes that govern its observable behavior. Filtering methods infer the latent state from observations. Classical filtering approaches, including Kalman filters, typically rely on simple observation models, such as linear-Gaussian models, that are incapable of characterizing the increasingly nonlinear and heterogeneous patterns in high-dimensional sensor signals. To tackle the challenge, we propose Generative Bayesian Filtering (GBF), a filtering framework that replaces restrictive observation models with pretrained","authors_text":"Jixin Yan, Lei Cao, Naichen Shi, Sihang Feng, Tao Sun","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-09T00:05:23Z","title":"Generative Bayesian Filtering for State Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.20521","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:b98832dcc11401822939000e512233ad7702429ede079e3619367668af2f7acd","target":"record","created_at":"2026-07-24T00:23:20Z","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":"3c63a28d54527c7e976cc95d7d5e995285bc2649489b57ad6cef2391662ec953","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-09T00:05:23Z","title_canon_sha256":"2204796cef84fa5708f15c1b82c1b330cf8e6bb012aa8119a92c432e7dca501d"},"schema_version":"1.0","source":{"id":"2607.20521","kind":"arxiv","version":1}},"canonical_sha256":"ee1cc4910e091d70ae1fb4023c550781958db9318ba49d48f1d0ed905db800c6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ee1cc4910e091d70ae1fb4023c550781958db9318ba49d48f1d0ed905db800c6","first_computed_at":"2026-07-24T00:23:20.242843Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-24T00:23:20.242843Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N8p31EyHiaBgSL067cJ366s99wHeefw1pSlN9ym2bLE7gBJgVqBK5mGuSuQGPy1ssZOb+ow+330WWUGeVxSIDA==","signature_status":"signed_v1","signed_at":"2026-07-24T00:23:20.243739Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.20521","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b98832dcc11401822939000e512233ad7702429ede079e3619367668af2f7acd","sha256:03d6a1ad420ed23af72b99679a94371caa934c0cc43a896f0e3ffa52918e6d40"],"state_sha256":"59826ff7db4ba5e8b5e3b63c71fbbb292a1e73d73bf7b463d60e495d7e993328"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TJ144foJX4Zm+EQWL+wuM43QmokKqmCtsJ6UvTpjnaoeMyy2MRWlQW7KtTHco4WmUFfQHr/InUOcXf+7WsKUDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T13:01:26.295511Z","bundle_sha256":"b377a8d1191605cdfa638c69f3d0d7399d54296bcec4077e7caf3b71eaf0e628"}}