{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:LSQQ435I6QQ7QE5D5S5EF4DZ6Y","short_pith_number":"pith:LSQQ435I","canonical_record":{"source":{"id":"2605.16391","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-12T05:03:52Z","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"title_canon_sha256":"e2041e3bf39f0d07b5cd944c1eead3258d4b517c9778915c0d1f480ce5f25b0f","abstract_canon_sha256":"10caab87475b7c5f73f6bf4919479404d146aeab89a406c5f145f4590dab9ada"},"schema_version":"1.0"},"canonical_sha256":"5ca10e6fa8f421f813a3ecba42f079f614c4300945807b7f20b4f3b61066443c","source":{"kind":"arxiv","id":"2605.16391","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.16391","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"arxiv_version","alias_value":"2605.16391v1","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16391","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"pith_short_12","alias_value":"LSQQ435I6QQ7","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"pith_short_16","alias_value":"LSQQ435I6QQ7QE5D","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"pith_short_8","alias_value":"LSQQ435I","created_at":"2026-05-20T00:02:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:LSQQ435I6QQ7QE5D5S5EF4DZ6Y","target":"record","payload":{"canonical_record":{"source":{"id":"2605.16391","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-12T05:03:52Z","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"title_canon_sha256":"e2041e3bf39f0d07b5cd944c1eead3258d4b517c9778915c0d1f480ce5f25b0f","abstract_canon_sha256":"10caab87475b7c5f73f6bf4919479404d146aeab89a406c5f145f4590dab9ada"},"schema_version":"1.0"},"canonical_sha256":"5ca10e6fa8f421f813a3ecba42f079f614c4300945807b7f20b4f3b61066443c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:02:19.951394Z","signature_b64":"ReJM0RYylqz0zttKpapT7vRiQKReB2yDODfL3YXw24QHYEIU2pWsB3pFaeT8EwufwBRrhMK/JH+do+lyHnRwCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5ca10e6fa8f421f813a3ecba42f079f614c4300945807b7f20b4f3b61066443c","last_reissued_at":"2026-05-20T00:02:19.950771Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:02:19.950771Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.16391","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":"2026-05-20T00:02:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PcSq6LpfiTag5WXEgece4L0KV+vFvNARwvQTssillE37T3mlIAXXjX2fwE7nZ1UX608SfzRVQxwEyDUS1Z87Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T13:02:09.093646Z"},"content_sha256":"d05f7c35f3021846858dffbbdbbc0d59eb3ce19332cf04405f2fbf6d750cc015","schema_version":"1.0","event_id":"sha256:d05f7c35f3021846858dffbbdbbc0d59eb3ce19332cf04405f2fbf6d750cc015"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:LSQQ435I6QQ7QE5D5S5EF4DZ6Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Overcoming the Intrinsic Performance Limitations of MEMS IMU via Diffusion-Based Generative Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG","cs.RO"],"primary_cat":"eess.SP","authors_text":"Feng Zhu, Jiarui Lv, Xiaohong Zhang","submitted_at":"2026-05-12T05:03:52Z","abstract_excerpt":"Inertial measurement units (IMUs) are fundamental sensing components in multi-source integrated navigation systems, and their performance directly determines the accuracy and reliability of solutions. However, the precision of low-cost IMUs is inherently constrained by hardware limitations. Recently, generative artificial intelligence has demonstrated remarkable capability in modeling complex data distributions and reconstructing high-fidelity signals. Motivated by this, we propose a diffusion-based generative learning framework for synthesizing high-fidelity virtual IMU data from low-cost IMU"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.16391","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/2605.16391/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T19:34:36.608118Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"8343140cfbc83a81f1a9df87cbda42b72551f32dcc08800aa33e3a028a96562a"},"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":"2026-05-20T00:02:19Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BX1alcXQNooyo15FZ0mQ3v5B2QuvkYi+KOuLmoZClG/NgnArpnh3/TD5HAlB5hqzaFX78ikGaT+cuJqyhQxICg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T13:02:09.094230Z"},"content_sha256":"14890b9cd98ac968ebfeb093a1b80e959bbf4fb8834077c7ee5e6422e1b3166c","schema_version":"1.0","event_id":"sha256:14890b9cd98ac968ebfeb093a1b80e959bbf4fb8834077c7ee5e6422e1b3166c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LSQQ435I6QQ7QE5D5S5EF4DZ6Y/bundle.json","state_url":"https://pith.science/pith/LSQQ435I6QQ7QE5D5S5EF4DZ6Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LSQQ435I6QQ7QE5D5S5EF4DZ6Y/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":"2026-06-11T13:02:09Z","links":{"resolver":"https://pith.science/pith/LSQQ435I6QQ7QE5D5S5EF4DZ6Y","bundle":"https://pith.science/pith/LSQQ435I6QQ7QE5D5S5EF4DZ6Y/bundle.json","state":"https://pith.science/pith/LSQQ435I6QQ7QE5D5S5EF4DZ6Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LSQQ435I6QQ7QE5D5S5EF4DZ6Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:LSQQ435I6QQ7QE5D5S5EF4DZ6Y","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":"10caab87475b7c5f73f6bf4919479404d146aeab89a406c5f145f4590dab9ada","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-12T05:03:52Z","title_canon_sha256":"e2041e3bf39f0d07b5cd944c1eead3258d4b517c9778915c0d1f480ce5f25b0f"},"schema_version":"1.0","source":{"id":"2605.16391","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.16391","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"arxiv_version","alias_value":"2605.16391v1","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.16391","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"pith_short_12","alias_value":"LSQQ435I6QQ7","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"pith_short_16","alias_value":"LSQQ435I6QQ7QE5D","created_at":"2026-05-20T00:02:19Z"},{"alias_kind":"pith_short_8","alias_value":"LSQQ435I","created_at":"2026-05-20T00:02:19Z"}],"graph_snapshots":[{"event_id":"sha256:14890b9cd98ac968ebfeb093a1b80e959bbf4fb8834077c7ee5e6422e1b3166c","target":"graph","created_at":"2026-05-20T00:02:19Z","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":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T19:34:36.608118Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.16391/integrity.json","findings":[],"snapshot_sha256":"8343140cfbc83a81f1a9df87cbda42b72551f32dcc08800aa33e3a028a96562a","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Inertial measurement units (IMUs) are fundamental sensing components in multi-source integrated navigation systems, and their performance directly determines the accuracy and reliability of solutions. However, the precision of low-cost IMUs is inherently constrained by hardware limitations. Recently, generative artificial intelligence has demonstrated remarkable capability in modeling complex data distributions and reconstructing high-fidelity signals. Motivated by this, we propose a diffusion-based generative learning framework for synthesizing high-fidelity virtual IMU data from low-cost IMU","authors_text":"Feng Zhu, Jiarui Lv, Xiaohong Zhang","cross_cats":["cs.AI","cs.LG","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-12T05:03:52Z","title":"Overcoming the Intrinsic Performance Limitations of MEMS IMU via Diffusion-Based Generative Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.16391","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:d05f7c35f3021846858dffbbdbbc0d59eb3ce19332cf04405f2fbf6d750cc015","target":"record","created_at":"2026-05-20T00:02:19Z","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":"10caab87475b7c5f73f6bf4919479404d146aeab89a406c5f145f4590dab9ada","cross_cats_sorted":["cs.AI","cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-12T05:03:52Z","title_canon_sha256":"e2041e3bf39f0d07b5cd944c1eead3258d4b517c9778915c0d1f480ce5f25b0f"},"schema_version":"1.0","source":{"id":"2605.16391","kind":"arxiv","version":1}},"canonical_sha256":"5ca10e6fa8f421f813a3ecba42f079f614c4300945807b7f20b4f3b61066443c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5ca10e6fa8f421f813a3ecba42f079f614c4300945807b7f20b4f3b61066443c","first_computed_at":"2026-05-20T00:02:19.950771Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:02:19.950771Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ReJM0RYylqz0zttKpapT7vRiQKReB2yDODfL3YXw24QHYEIU2pWsB3pFaeT8EwufwBRrhMK/JH+do+lyHnRwCw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:02:19.951394Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.16391","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d05f7c35f3021846858dffbbdbbc0d59eb3ce19332cf04405f2fbf6d750cc015","sha256:14890b9cd98ac968ebfeb093a1b80e959bbf4fb8834077c7ee5e6422e1b3166c"],"state_sha256":"b9cba2f8297183127d4c64ecb0b892bb470eb8955b85884f86ce65ffb9132880"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7+MyKQyEZEcXW7FfSX5WKGKi+8fJF+Gk/hNGTmmbICYIewklztoITMLxggxSzBcNbDnQZY1PCHx03aov8R3mBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T13:02:09.096761Z","bundle_sha256":"79e250e7f679c01dfa4635fceaf644cd6cf03a3784f3fe8378c6fac8eb177cda"}}