{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:YPTBU6QSHVZ4GNHT25CKD2JGZR","short_pith_number":"pith:YPTBU6QS","canonical_record":{"source":{"id":"2502.05629","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-08T16:21:18Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"d32811073237c40dc0b680788b33b0f5c034d34236602f13183fba1ab609ba54","abstract_canon_sha256":"bcc29c2410865a0f079c07c66403e069fa081707f074c918a50b117b8c16b77b"},"schema_version":"1.0"},"canonical_sha256":"c3e61a7a123d73c334f3d744a1e926cc6b1ad538b7680ae8998e3d6673d02c3a","source":{"kind":"arxiv","id":"2502.05629","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.05629","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"arxiv_version","alias_value":"2502.05629v1","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05629","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"pith_short_12","alias_value":"YPTBU6QSHVZ4","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"pith_short_16","alias_value":"YPTBU6QSHVZ4GNHT","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"pith_short_8","alias_value":"YPTBU6QS","created_at":"2026-07-05T10:11:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:YPTBU6QSHVZ4GNHT25CKD2JGZR","target":"record","payload":{"canonical_record":{"source":{"id":"2502.05629","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-08T16:21:18Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"d32811073237c40dc0b680788b33b0f5c034d34236602f13183fba1ab609ba54","abstract_canon_sha256":"bcc29c2410865a0f079c07c66403e069fa081707f074c918a50b117b8c16b77b"},"schema_version":"1.0"},"canonical_sha256":"c3e61a7a123d73c334f3d744a1e926cc6b1ad538b7680ae8998e3d6673d02c3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:11:40.777562Z","signature_b64":"TzfsAuSJ/9pkisuXfLPV+EoxOWkK2Lm/83CbFCKV5ycLHlQPNGxKmYREyPgyT7ohOaOsz+LvfHgOIFSah/TPDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c3e61a7a123d73c334f3d744a1e926cc6b1ad538b7680ae8998e3d6673d02c3a","last_reissued_at":"2026-07-05T10:11:40.777081Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:11:40.777081Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.05629","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":"2026-07-05T10:11:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DR3Y9c248TVtZaX4NctN/e70nTyZPo324CZAru/zvW8rIZIC2SpGzu8gRId0yp0VXdrHPfMjJA1ho2+qKJhGDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T09:43:24.441652Z"},"content_sha256":"46c2e08045e982da399b56a945043b244db970dad8bd494f48f8c84917857b3f","schema_version":"1.0","event_id":"sha256:46c2e08045e982da399b56a945043b244db970dad8bd494f48f8c84917857b3f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:YPTBU6QSHVZ4GNHT25CKD2JGZR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TrackDiffuser: Nearly Model-Free Bayesian Filtering with Diffusion Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.SP"],"primary_cat":"cs.LG","authors_text":"Bo Jin, Juan Zhang, Minzhe Li, Wenhao Li, Xiangfeng Wang, Yangguang He","submitted_at":"2025-02-08T16:21:18Z","abstract_excerpt":"State estimation remains a fundamental challenge across numerous domains, from autonomous driving, aircraft tracking to quantum system control. Although Bayesian filtering has been the cornerstone solution, its classical model-based paradigm faces two major limitations: it struggles with inaccurate state space model (SSM) and requires extensive prior knowledge of noise characteristics. We present TrackDiffuser, a generative framework addressing both challenges by reformulating Bayesian filtering as a conditional diffusion model. Our approach implicitly learns system dynamics from data to mitig"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05629","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/2502.05629/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":"2026-07-05T10:11:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e5xxyz10WQWSHCvtCkQdro5dDUgBOnUsVp3LPAJ4run4ya+8gOS1c53s7XRDrx5Re7oGth+Lgv2uXTwg8M1KDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T09:43:24.442025Z"},"content_sha256":"5a89d5e7598f8a10486a050a2d687b308528e7cd2e957079b99a1e94702f4843","schema_version":"1.0","event_id":"sha256:5a89d5e7598f8a10486a050a2d687b308528e7cd2e957079b99a1e94702f4843"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YPTBU6QSHVZ4GNHT25CKD2JGZR/bundle.json","state_url":"https://pith.science/pith/YPTBU6QSHVZ4GNHT25CKD2JGZR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YPTBU6QSHVZ4GNHT25CKD2JGZR/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":"2026-07-07T09:43:24Z","links":{"resolver":"https://pith.science/pith/YPTBU6QSHVZ4GNHT25CKD2JGZR","bundle":"https://pith.science/pith/YPTBU6QSHVZ4GNHT25CKD2JGZR/bundle.json","state":"https://pith.science/pith/YPTBU6QSHVZ4GNHT25CKD2JGZR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YPTBU6QSHVZ4GNHT25CKD2JGZR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YPTBU6QSHVZ4GNHT25CKD2JGZR","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":"bcc29c2410865a0f079c07c66403e069fa081707f074c918a50b117b8c16b77b","cross_cats_sorted":["eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-08T16:21:18Z","title_canon_sha256":"d32811073237c40dc0b680788b33b0f5c034d34236602f13183fba1ab609ba54"},"schema_version":"1.0","source":{"id":"2502.05629","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.05629","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"arxiv_version","alias_value":"2502.05629v1","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05629","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"pith_short_12","alias_value":"YPTBU6QSHVZ4","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"pith_short_16","alias_value":"YPTBU6QSHVZ4GNHT","created_at":"2026-07-05T10:11:40Z"},{"alias_kind":"pith_short_8","alias_value":"YPTBU6QS","created_at":"2026-07-05T10:11:40Z"}],"graph_snapshots":[{"event_id":"sha256:5a89d5e7598f8a10486a050a2d687b308528e7cd2e957079b99a1e94702f4843","target":"graph","created_at":"2026-07-05T10:11:40Z","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/2502.05629/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"State estimation remains a fundamental challenge across numerous domains, from autonomous driving, aircraft tracking to quantum system control. Although Bayesian filtering has been the cornerstone solution, its classical model-based paradigm faces two major limitations: it struggles with inaccurate state space model (SSM) and requires extensive prior knowledge of noise characteristics. We present TrackDiffuser, a generative framework addressing both challenges by reformulating Bayesian filtering as a conditional diffusion model. Our approach implicitly learns system dynamics from data to mitig","authors_text":"Bo Jin, Juan Zhang, Minzhe Li, Wenhao Li, Xiangfeng Wang, Yangguang He","cross_cats":["eess.SP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-08T16:21:18Z","title":"TrackDiffuser: Nearly Model-Free Bayesian Filtering with Diffusion Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05629","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":"sha256:46c2e08045e982da399b56a945043b244db970dad8bd494f48f8c84917857b3f","target":"record","created_at":"2026-07-05T10:11:40Z","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":"bcc29c2410865a0f079c07c66403e069fa081707f074c918a50b117b8c16b77b","cross_cats_sorted":["eess.SP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-02-08T16:21:18Z","title_canon_sha256":"d32811073237c40dc0b680788b33b0f5c034d34236602f13183fba1ab609ba54"},"schema_version":"1.0","source":{"id":"2502.05629","kind":"arxiv","version":1}},"canonical_sha256":"c3e61a7a123d73c334f3d744a1e926cc6b1ad538b7680ae8998e3d6673d02c3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c3e61a7a123d73c334f3d744a1e926cc6b1ad538b7680ae8998e3d6673d02c3a","first_computed_at":"2026-07-05T10:11:40.777081Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:11:40.777081Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TzfsAuSJ/9pkisuXfLPV+EoxOWkK2Lm/83CbFCKV5ycLHlQPNGxKmYREyPgyT7ohOaOsz+LvfHgOIFSah/TPDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:11:40.777562Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.05629","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:46c2e08045e982da399b56a945043b244db970dad8bd494f48f8c84917857b3f","sha256:5a89d5e7598f8a10486a050a2d687b308528e7cd2e957079b99a1e94702f4843"],"state_sha256":"ae84afc110732c11c839b32c84064e506ac39e1ac808085ccf555dfee547089b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QiOXDS9qc8w5RsxrRpaaA/lQmZnFgEz0rBVsQ0azxpvI/sSIwkDFK1SEP3dVEPYw63H1kUqYPUt+UmbY5Q8hCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T09:43:24.443930Z","bundle_sha256":"414fa663764ac568479b52bf42ba7132414321ad8dc14a913bb7fc4536a9e20b"}}