{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:C23Q5PIBFLHKKJTUEI6WCYH4W3","short_pith_number":"pith:C23Q5PIB","canonical_record":{"source":{"id":"2606.25627","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T09:34:27Z","cross_cats_sorted":["cs.AI","cs.CR","cs.DC"],"title_canon_sha256":"b466f0c31032c5faaa541b01ab159adbaadf6bbd6c07b5bfa2955d937c6d26f2","abstract_canon_sha256":"06fc8b15d7fa110af1d655d1722a0892916f1f97c171f4bcbb683e859a356e5e"},"schema_version":"1.0"},"canonical_sha256":"16b70ebd012acea52674223d6160fcb6d4e3436e49a28754b8137f23841d56a5","source":{"kind":"arxiv","id":"2606.25627","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25627","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25627v1","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25627","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"pith_short_12","alias_value":"C23Q5PIBFLHK","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"pith_short_16","alias_value":"C23Q5PIBFLHKKJTU","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"pith_short_8","alias_value":"C23Q5PIB","created_at":"2026-06-25T01:18:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:C23Q5PIBFLHKKJTUEI6WCYH4W3","target":"record","payload":{"canonical_record":{"source":{"id":"2606.25627","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T09:34:27Z","cross_cats_sorted":["cs.AI","cs.CR","cs.DC"],"title_canon_sha256":"b466f0c31032c5faaa541b01ab159adbaadf6bbd6c07b5bfa2955d937c6d26f2","abstract_canon_sha256":"06fc8b15d7fa110af1d655d1722a0892916f1f97c171f4bcbb683e859a356e5e"},"schema_version":"1.0"},"canonical_sha256":"16b70ebd012acea52674223d6160fcb6d4e3436e49a28754b8137f23841d56a5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-25T01:18:10.828178Z","signature_b64":"bjjBGOl20Winx8tm9Iiru+mHtig1bWPVJgQJK7/C9R/GI1DOkz5I751Jefa69f1nvkhixH78Mbu3anXAy9NsBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"16b70ebd012acea52674223d6160fcb6d4e3436e49a28754b8137f23841d56a5","last_reissued_at":"2026-06-25T01:18:10.827731Z","signature_status":"signed_v1","first_computed_at":"2026-06-25T01:18:10.827731Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.25627","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":"2026-06-25T01:18:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AoMrkuHA86NH0XcmqDILVAeUT/llx04pTSIMoGmmGdhb/4OIwlkpCspSfTidNgUxw5J4eoUGEovhL7IJRmaiDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T11:33:54.983672Z"},"content_sha256":"a796d2d64b052b22f7772abfb3adcae207ec67a5e941778e7021a785d3f4f027","schema_version":"1.0","event_id":"sha256:a796d2d64b052b22f7772abfb3adcae207ec67a5e941778e7021a785d3f4f027"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:C23Q5PIBFLHKKJTUEI6WCYH4W3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TL++: Accuracy and Privacy Preserving Traversal Learning for Distributed Intelligent Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CR","cs.DC"],"primary_cat":"cs.LG","authors_text":"Erdenebileg Batbaatar, Young Yoon","submitted_at":"2026-06-24T09:34:27Z","abstract_excerpt":"Distributed intelligent systems increasingly need to train across data silos without centralizing raw data. Federated learning keeps data local but can suffer under heterogeneous partitions and requires repeated full-model exchange. Split learning reduces communication through cut-layer activations, but standard protocols generally do not recover centralized mini-batch gradient behavior and may expose activations and gradients in plaintext. We present TL++, a two-mode traversal-learning framework that constructs virtual batches across nodes to recover centralized mini-batch gradient behavior u"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25627","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/2606.25627/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":"2026-06-25T01:18:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RJlOWelWR4er+y5ZnScYf5VykIeA03VBVjy5EeR4Z1PeKoZsO2+R9qxBzUUCPZ2ip1Gjjg2MlEDpCYiBR0ZJCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T11:33:54.984043Z"},"content_sha256":"8187ffc95444ce2581e5c068afff5a66b0ee33838f0cb4a5a9891ebd94957045","schema_version":"1.0","event_id":"sha256:8187ffc95444ce2581e5c068afff5a66b0ee33838f0cb4a5a9891ebd94957045"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C23Q5PIBFLHKKJTUEI6WCYH4W3/bundle.json","state_url":"https://pith.science/pith/C23Q5PIBFLHKKJTUEI6WCYH4W3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C23Q5PIBFLHKKJTUEI6WCYH4W3/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":"2026-06-29T11:33:54Z","links":{"resolver":"https://pith.science/pith/C23Q5PIBFLHKKJTUEI6WCYH4W3","bundle":"https://pith.science/pith/C23Q5PIBFLHKKJTUEI6WCYH4W3/bundle.json","state":"https://pith.science/pith/C23Q5PIBFLHKKJTUEI6WCYH4W3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C23Q5PIBFLHKKJTUEI6WCYH4W3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:C23Q5PIBFLHKKJTUEI6WCYH4W3","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":"06fc8b15d7fa110af1d655d1722a0892916f1f97c171f4bcbb683e859a356e5e","cross_cats_sorted":["cs.AI","cs.CR","cs.DC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T09:34:27Z","title_canon_sha256":"b466f0c31032c5faaa541b01ab159adbaadf6bbd6c07b5bfa2955d937c6d26f2"},"schema_version":"1.0","source":{"id":"2606.25627","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.25627","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"arxiv_version","alias_value":"2606.25627v1","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.25627","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"pith_short_12","alias_value":"C23Q5PIBFLHK","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"pith_short_16","alias_value":"C23Q5PIBFLHKKJTU","created_at":"2026-06-25T01:18:10Z"},{"alias_kind":"pith_short_8","alias_value":"C23Q5PIB","created_at":"2026-06-25T01:18:10Z"}],"graph_snapshots":[{"event_id":"sha256:8187ffc95444ce2581e5c068afff5a66b0ee33838f0cb4a5a9891ebd94957045","target":"graph","created_at":"2026-06-25T01:18:10Z","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/2606.25627/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Distributed intelligent systems increasingly need to train across data silos without centralizing raw data. Federated learning keeps data local but can suffer under heterogeneous partitions and requires repeated full-model exchange. Split learning reduces communication through cut-layer activations, but standard protocols generally do not recover centralized mini-batch gradient behavior and may expose activations and gradients in plaintext. We present TL++, a two-mode traversal-learning framework that constructs virtual batches across nodes to recover centralized mini-batch gradient behavior u","authors_text":"Erdenebileg Batbaatar, Young Yoon","cross_cats":["cs.AI","cs.CR","cs.DC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T09:34:27Z","title":"TL++: Accuracy and Privacy Preserving Traversal Learning for Distributed Intelligent Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.25627","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:a796d2d64b052b22f7772abfb3adcae207ec67a5e941778e7021a785d3f4f027","target":"record","created_at":"2026-06-25T01:18:10Z","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":"06fc8b15d7fa110af1d655d1722a0892916f1f97c171f4bcbb683e859a356e5e","cross_cats_sorted":["cs.AI","cs.CR","cs.DC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-24T09:34:27Z","title_canon_sha256":"b466f0c31032c5faaa541b01ab159adbaadf6bbd6c07b5bfa2955d937c6d26f2"},"schema_version":"1.0","source":{"id":"2606.25627","kind":"arxiv","version":1}},"canonical_sha256":"16b70ebd012acea52674223d6160fcb6d4e3436e49a28754b8137f23841d56a5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"16b70ebd012acea52674223d6160fcb6d4e3436e49a28754b8137f23841d56a5","first_computed_at":"2026-06-25T01:18:10.827731Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-25T01:18:10.827731Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bjjBGOl20Winx8tm9Iiru+mHtig1bWPVJgQJK7/C9R/GI1DOkz5I751Jefa69f1nvkhixH78Mbu3anXAy9NsBA==","signature_status":"signed_v1","signed_at":"2026-06-25T01:18:10.828178Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.25627","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a796d2d64b052b22f7772abfb3adcae207ec67a5e941778e7021a785d3f4f027","sha256:8187ffc95444ce2581e5c068afff5a66b0ee33838f0cb4a5a9891ebd94957045"],"state_sha256":"8cb85d3377407be67a24ee1a518524b0d0d4b690fa335487574555527eb427c1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xTQKdrjTZXNm3jv1fzTSEoMmkJuoCBCkaw2zC2ZJD/O1p7+xJ5aSk0HqX+SdQ+/vayq0boIvHripRn0evyPFCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T11:33:54.986051Z","bundle_sha256":"d41684cd04b65d6cc366f67f51a72c36f0b2356e1e7dca10ee50d5595a71fa3c"}}