{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:AMTTLVT7TEONZIRL6OK5DHZ234","short_pith_number":"pith:AMTTLVT7","canonical_record":{"source":{"id":"2411.11519","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2024-11-18T12:27:20Z","cross_cats_sorted":[],"title_canon_sha256":"76bb028d950c8e00bebc5cb6ee2e47e36fbf87abdbeb3455959f32fa683190bc","abstract_canon_sha256":"58c2c7a44749f9a441f888aa22e055bde871f0a5d23328cf70457a06c4fbb96a"},"schema_version":"1.0"},"canonical_sha256":"032735d67f991cdca22bf395d19f3adf01aa9405b3480392e3340b19613c36db","source":{"kind":"arxiv","id":"2411.11519","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.11519","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"arxiv_version","alias_value":"2411.11519v1","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.11519","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"pith_short_12","alias_value":"AMTTLVT7TEON","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"pith_short_16","alias_value":"AMTTLVT7TEONZIRL","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"pith_short_8","alias_value":"AMTTLVT7","created_at":"2026-07-05T09:36:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:AMTTLVT7TEONZIRL6OK5DHZ234","target":"record","payload":{"canonical_record":{"source":{"id":"2411.11519","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2024-11-18T12:27:20Z","cross_cats_sorted":[],"title_canon_sha256":"76bb028d950c8e00bebc5cb6ee2e47e36fbf87abdbeb3455959f32fa683190bc","abstract_canon_sha256":"58c2c7a44749f9a441f888aa22e055bde871f0a5d23328cf70457a06c4fbb96a"},"schema_version":"1.0"},"canonical_sha256":"032735d67f991cdca22bf395d19f3adf01aa9405b3480392e3340b19613c36db","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:36:57.457532Z","signature_b64":"PMaPBS1pHC8iW0kx5Y/y9HO5QGzADdq2f+TiP1M7sFLdwhB6G+MQ36Ih9/Y1yQGi3eRjOzwdU+OWkSwTkO75CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"032735d67f991cdca22bf395d19f3adf01aa9405b3480392e3340b19613c36db","last_reissued_at":"2026-07-05T09:36:57.456944Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:36:57.456944Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.11519","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":"2026-07-05T09:36:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jePsCwEETosj8UkopJeKpdpU2gAhKRiNWG11N69ofZMOXo3y1qU18HCIJqFcUdDpyI04xS+Yr4R9St5zFGFGBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T17:58:03.994560Z"},"content_sha256":"9b63de986b7aec9425f55ba6fc9ce78ffe1518d02f282760152a473143eae169","schema_version":"1.0","event_id":"sha256:9b63de986b7aec9425f55ba6fc9ce78ffe1518d02f282760152a473143eae169"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:AMTTLVT7TEONZIRL6OK5DHZ234","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Transformer networks for Heavy flavor jet tagging","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"hep-ph","authors_text":"A. Hammad, Mihoko M Nojiri","submitted_at":"2024-11-18T12:27:20Z","abstract_excerpt":"In this article, we review recent machine learning methods used in challenging particle identification of heavy-boosted particles at high-energy colliders. Our primary focus is on attention-based Transformer networks. We report the performance of state-of-the-art deep learning networks and further improvement coming from the modification of networks based on physics insights. Additionally, we discuss interpretable methods to understand network decision-making, which are crucial when employing highly complex and deep networks."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.11519","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/2411.11519/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":"2026-07-05T09:36:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7g2Vp9LqffC5e21tM96c66lENqQVpfgbZO9zwJE4yVqL+hp8jHm820ImROR9hR+KzFVRbPHBluBKBnpXmAugCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T17:58:03.994989Z"},"content_sha256":"ff3c0d90db41151dc7c6356859363fd6888d699af56371d3b1c8a62912ffb498","schema_version":"1.0","event_id":"sha256:ff3c0d90db41151dc7c6356859363fd6888d699af56371d3b1c8a62912ffb498"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AMTTLVT7TEONZIRL6OK5DHZ234/bundle.json","state_url":"https://pith.science/pith/AMTTLVT7TEONZIRL6OK5DHZ234/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AMTTLVT7TEONZIRL6OK5DHZ234/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":"2026-08-13T17:58:03Z","links":{"resolver":"https://pith.science/pith/AMTTLVT7TEONZIRL6OK5DHZ234","bundle":"https://pith.science/pith/AMTTLVT7TEONZIRL6OK5DHZ234/bundle.json","state":"https://pith.science/pith/AMTTLVT7TEONZIRL6OK5DHZ234/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AMTTLVT7TEONZIRL6OK5DHZ234/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:AMTTLVT7TEONZIRL6OK5DHZ234","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":"58c2c7a44749f9a441f888aa22e055bde871f0a5d23328cf70457a06c4fbb96a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2024-11-18T12:27:20Z","title_canon_sha256":"76bb028d950c8e00bebc5cb6ee2e47e36fbf87abdbeb3455959f32fa683190bc"},"schema_version":"1.0","source":{"id":"2411.11519","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.11519","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"arxiv_version","alias_value":"2411.11519v1","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.11519","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"pith_short_12","alias_value":"AMTTLVT7TEON","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"pith_short_16","alias_value":"AMTTLVT7TEONZIRL","created_at":"2026-07-05T09:36:57Z"},{"alias_kind":"pith_short_8","alias_value":"AMTTLVT7","created_at":"2026-07-05T09:36:57Z"}],"graph_snapshots":[{"event_id":"sha256:ff3c0d90db41151dc7c6356859363fd6888d699af56371d3b1c8a62912ffb498","target":"graph","created_at":"2026-07-05T09:36:57Z","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/2411.11519/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this article, we review recent machine learning methods used in challenging particle identification of heavy-boosted particles at high-energy colliders. Our primary focus is on attention-based Transformer networks. We report the performance of state-of-the-art deep learning networks and further improvement coming from the modification of networks based on physics insights. Additionally, we discuss interpretable methods to understand network decision-making, which are crucial when employing highly complex and deep networks.","authors_text":"A. Hammad, Mihoko M Nojiri","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2024-11-18T12:27:20Z","title":"Transformer networks for Heavy flavor jet tagging"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.11519","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":"sha256:9b63de986b7aec9425f55ba6fc9ce78ffe1518d02f282760152a473143eae169","target":"record","created_at":"2026-07-05T09:36:57Z","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":"58c2c7a44749f9a441f888aa22e055bde871f0a5d23328cf70457a06c4fbb96a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"hep-ph","submitted_at":"2024-11-18T12:27:20Z","title_canon_sha256":"76bb028d950c8e00bebc5cb6ee2e47e36fbf87abdbeb3455959f32fa683190bc"},"schema_version":"1.0","source":{"id":"2411.11519","kind":"arxiv","version":1}},"canonical_sha256":"032735d67f991cdca22bf395d19f3adf01aa9405b3480392e3340b19613c36db","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"032735d67f991cdca22bf395d19f3adf01aa9405b3480392e3340b19613c36db","first_computed_at":"2026-07-05T09:36:57.456944Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:36:57.456944Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PMaPBS1pHC8iW0kx5Y/y9HO5QGzADdq2f+TiP1M7sFLdwhB6G+MQ36Ih9/Y1yQGi3eRjOzwdU+OWkSwTkO75CA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:36:57.457532Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.11519","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9b63de986b7aec9425f55ba6fc9ce78ffe1518d02f282760152a473143eae169","sha256:ff3c0d90db41151dc7c6356859363fd6888d699af56371d3b1c8a62912ffb498"],"state_sha256":"14cf40d6cac3f69df12334b2921ff3a5c5fa8e23a0708b792742100d4b4030d7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2k90NdtJGqsTychoVAPVCMLCd5I9Ngg8/4NoJZ/1+FQ0Lw/zhd4y5cdS0q7Sm7wvLm8uDobOQg7kGV1btm9pDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T17:58:03.998004Z","bundle_sha256":"455c642f4d5dd5e4bcb0a11bb223cd88d02e361aa18ecbd60a5d0780e6556627"}}