{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:V7B5I3VJU67LFLZM2FEATKXIF2","short_pith_number":"pith:V7B5I3VJ","canonical_record":{"source":{"id":"2405.03060","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T21:49:51Z","cross_cats_sorted":[],"title_canon_sha256":"4a6c2c2f792dedca81703b07fa8876cf24fd27aca06f94f79eb0936564095de4","abstract_canon_sha256":"b4326103c1decdea09672e618ccd0d9a90dcccb8d9d36a800a54e9d45f6b00ed"},"schema_version":"1.0"},"canonical_sha256":"afc3d46ea9a7beb2af2cd14809aae82eb03391f72c481ebdae2889ef5c4cc956","source":{"kind":"arxiv","id":"2405.03060","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.03060","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"arxiv_version","alias_value":"2405.03060v1","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.03060","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_12","alias_value":"V7B5I3VJU67L","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_16","alias_value":"V7B5I3VJU67LFLZM","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_8","alias_value":"V7B5I3VJ","created_at":"2026-07-05T08:15:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:V7B5I3VJU67LFLZM2FEATKXIF2","target":"record","payload":{"canonical_record":{"source":{"id":"2405.03060","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T21:49:51Z","cross_cats_sorted":[],"title_canon_sha256":"4a6c2c2f792dedca81703b07fa8876cf24fd27aca06f94f79eb0936564095de4","abstract_canon_sha256":"b4326103c1decdea09672e618ccd0d9a90dcccb8d9d36a800a54e9d45f6b00ed"},"schema_version":"1.0"},"canonical_sha256":"afc3d46ea9a7beb2af2cd14809aae82eb03391f72c481ebdae2889ef5c4cc956","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:15:57.907853Z","signature_b64":"iHkVpWxZElwmSQjzHXJ+qNAYtSK6PWBLYKXEryRBJXN6BgFVQxyXIMujkijJBmcNPeHExnQTYYK+n5bXHlzdAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"afc3d46ea9a7beb2af2cd14809aae82eb03391f72c481ebdae2889ef5c4cc956","last_reissued_at":"2026-07-05T08:15:57.907449Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:15:57.907449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.03060","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":"2026-07-05T08:15:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dZIK2ntnuc2G8URVGzksv8olDDj+b7+17oWzrIbzT8JZzbmI+/2MNB9yKQkdsTkn8pICB2bK8NIeqLnUQYU5DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T03:38:55.341610Z"},"content_sha256":"f9d9e5603f42cd30787f05feef256000182b346b87b6da686f751daca4efdb87","schema_version":"1.0","event_id":"sha256:f9d9e5603f42cd30787f05feef256000182b346b87b6da686f751daca4efdb87"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:V7B5I3VJU67LFLZM2FEATKXIF2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Tree-based Ensemble Learning for Out-of-distribution Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Guang Cheng, Hao Zhu, Lin Mu, Menglun Wang, Ming-Jun Lai, Qi Liu, Ruihao Huang, Zhaiming Shen","submitted_at":"2024-05-05T21:49:51Z","abstract_excerpt":"Being able to successfully determine whether the testing samples has similar distribution as the training samples is a fundamental question to address before we can safely deploy most of the machine learning models into practice. In this paper, we propose TOOD detection, a simple yet effective tree-based out-of-distribution (TOOD) detection mechanism to determine if a set of unseen samples will have similar distribution as of the training samples. The TOOD detection mechanism is based on computing pairwise hamming distance of testing samples' tree embeddings, which are obtained by fitting a tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.03060","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/2405.03060/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":"2026-07-05T08:15:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ozrjpQSXG+c9XTubMIqYqhQxDCAif7H7SZMVzBSvsLaub8vYKXvYqI60NVIkCPg9i5YimeJyNxBO4N8li6RmCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T03:38:55.342183Z"},"content_sha256":"37b972f5dc4f712864dd185ff9fc9970d8650f70abf3d4eb0163d7c0b0502685","schema_version":"1.0","event_id":"sha256:37b972f5dc4f712864dd185ff9fc9970d8650f70abf3d4eb0163d7c0b0502685"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V7B5I3VJU67LFLZM2FEATKXIF2/bundle.json","state_url":"https://pith.science/pith/V7B5I3VJU67LFLZM2FEATKXIF2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V7B5I3VJU67LFLZM2FEATKXIF2/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":"2026-08-07T03:38:55Z","links":{"resolver":"https://pith.science/pith/V7B5I3VJU67LFLZM2FEATKXIF2","bundle":"https://pith.science/pith/V7B5I3VJU67LFLZM2FEATKXIF2/bundle.json","state":"https://pith.science/pith/V7B5I3VJU67LFLZM2FEATKXIF2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V7B5I3VJU67LFLZM2FEATKXIF2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:V7B5I3VJU67LFLZM2FEATKXIF2","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":"b4326103c1decdea09672e618ccd0d9a90dcccb8d9d36a800a54e9d45f6b00ed","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T21:49:51Z","title_canon_sha256":"4a6c2c2f792dedca81703b07fa8876cf24fd27aca06f94f79eb0936564095de4"},"schema_version":"1.0","source":{"id":"2405.03060","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.03060","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"arxiv_version","alias_value":"2405.03060v1","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.03060","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_12","alias_value":"V7B5I3VJU67L","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_16","alias_value":"V7B5I3VJU67LFLZM","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_8","alias_value":"V7B5I3VJ","created_at":"2026-07-05T08:15:57Z"}],"graph_snapshots":[{"event_id":"sha256:37b972f5dc4f712864dd185ff9fc9970d8650f70abf3d4eb0163d7c0b0502685","target":"graph","created_at":"2026-07-05T08:15:57Z","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/2405.03060/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Being able to successfully determine whether the testing samples has similar distribution as the training samples is a fundamental question to address before we can safely deploy most of the machine learning models into practice. In this paper, we propose TOOD detection, a simple yet effective tree-based out-of-distribution (TOOD) detection mechanism to determine if a set of unseen samples will have similar distribution as of the training samples. The TOOD detection mechanism is based on computing pairwise hamming distance of testing samples' tree embeddings, which are obtained by fitting a tr","authors_text":"Guang Cheng, Hao Zhu, Lin Mu, Menglun Wang, Ming-Jun Lai, Qi Liu, Ruihao Huang, Zhaiming Shen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T21:49:51Z","title":"Tree-based Ensemble Learning for Out-of-distribution Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.03060","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:f9d9e5603f42cd30787f05feef256000182b346b87b6da686f751daca4efdb87","target":"record","created_at":"2026-07-05T08:15:57Z","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":"b4326103c1decdea09672e618ccd0d9a90dcccb8d9d36a800a54e9d45f6b00ed","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T21:49:51Z","title_canon_sha256":"4a6c2c2f792dedca81703b07fa8876cf24fd27aca06f94f79eb0936564095de4"},"schema_version":"1.0","source":{"id":"2405.03060","kind":"arxiv","version":1}},"canonical_sha256":"afc3d46ea9a7beb2af2cd14809aae82eb03391f72c481ebdae2889ef5c4cc956","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"afc3d46ea9a7beb2af2cd14809aae82eb03391f72c481ebdae2889ef5c4cc956","first_computed_at":"2026-07-05T08:15:57.907449Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:15:57.907449Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iHkVpWxZElwmSQjzHXJ+qNAYtSK6PWBLYKXEryRBJXN6BgFVQxyXIMujkijJBmcNPeHExnQTYYK+n5bXHlzdAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:15:57.907853Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.03060","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f9d9e5603f42cd30787f05feef256000182b346b87b6da686f751daca4efdb87","sha256:37b972f5dc4f712864dd185ff9fc9970d8650f70abf3d4eb0163d7c0b0502685"],"state_sha256":"0e351804273c9a9b2cfbfde84b907c6c6ca604ff351c6320cf6bc9e6ceb5edff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GH5uRTIVeZXHe878GyHt2dt/dB3RGPGAQzYH1qkl19wA9Dc/jGobYGngS1eW6gVl6VVsqG318JL7jb0riFSZAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T03:38:55.347598Z","bundle_sha256":"ed1e9185d5848ac3fc52426cd29d139e878f0c33adb84ab9d77991e813b719cf"}}