{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:NEIO3OTBHJGJPLILFLR2ZYY2QM","short_pith_number":"pith:NEIO3OTB","schema_version":"1.0","canonical_sha256":"6910edba613a4c97ad0b2ae3ace31a833af24ac855bad72434e1dbb1ff839c33","source":{"kind":"arxiv","id":"2505.15391","version":1},"attestation_state":"computed","paper":{"title":"InTreeger: An End-to-End Framework for Integer-Only Decision Tree Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Ana-Lucia Varbanescu, Bruno Endres Forlin, Duncan Bart, Kuan-Hsun Chen, Marco Ottavi","submitted_at":"2025-05-21T11:28:43Z","abstract_excerpt":"Integer quantization has emerged as a critical technique to facilitate deployment on resource-constrained devices. Although they do reduce the complexity of the learning models, their inference performance is often prone to quantization-induced errors. To this end, we introduce InTreeger: an end-to-end framework that takes a training dataset as input, and outputs an architecture-agnostic integer-only C implementation of tree-based machine learning model, without loss of precision. This framework enables anyone, even those without prior experience in machine learning, to generate a highly optim"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2505.15391","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-05-21T11:28:43Z","cross_cats_sorted":[],"title_canon_sha256":"7d9b5ead50e0ba35ad8e04ad501d4b7fd7b946c84f208f7f96e4cf3b40d813aa","abstract_canon_sha256":"8935fd580e67444838b6af0097fad820bdfe09f02ad1e20147e42b47ea514a32"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:06:44.626827Z","signature_b64":"GfAbaAjleHH9wJR74hGPb6tV1rURn19KvYpKyXIKKd1itvJeoMC3J1LmT6LKU61ED/3S1tXpt+vCZBxUTXMqCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6910edba613a4c97ad0b2ae3ace31a833af24ac855bad72434e1dbb1ff839c33","last_reissued_at":"2026-07-05T11:06:44.626355Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:06:44.626355Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"InTreeger: An End-to-End Framework for Integer-Only Decision Tree Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Ana-Lucia Varbanescu, Bruno Endres Forlin, Duncan Bart, Kuan-Hsun Chen, Marco Ottavi","submitted_at":"2025-05-21T11:28:43Z","abstract_excerpt":"Integer quantization has emerged as a critical technique to facilitate deployment on resource-constrained devices. Although they do reduce the complexity of the learning models, their inference performance is often prone to quantization-induced errors. To this end, we introduce InTreeger: an end-to-end framework that takes a training dataset as input, and outputs an architecture-agnostic integer-only C implementation of tree-based machine learning model, without loss of precision. This framework enables anyone, even those without prior experience in machine learning, to generate a highly optim"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.15391","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/2505.15391/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2505.15391","created_at":"2026-07-05T11:06:44.626417+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.15391v1","created_at":"2026-07-05T11:06:44.626417+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.15391","created_at":"2026-07-05T11:06:44.626417+00:00"},{"alias_kind":"pith_short_12","alias_value":"NEIO3OTBHJGJ","created_at":"2026-07-05T11:06:44.626417+00:00"},{"alias_kind":"pith_short_16","alias_value":"NEIO3OTBHJGJPLIL","created_at":"2026-07-05T11:06:44.626417+00:00"},{"alias_kind":"pith_short_8","alias_value":"NEIO3OTB","created_at":"2026-07-05T11:06:44.626417+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/NEIO3OTBHJGJPLILFLR2ZYY2QM","json":"https://pith.science/pith/NEIO3OTBHJGJPLILFLR2ZYY2QM.json","graph_json":"https://pith.science/api/pith-number/NEIO3OTBHJGJPLILFLR2ZYY2QM/graph.json","events_json":"https://pith.science/api/pith-number/NEIO3OTBHJGJPLILFLR2ZYY2QM/events.json","paper":"https://pith.science/paper/NEIO3OTB"},"agent_actions":{"view_html":"https://pith.science/pith/NEIO3OTBHJGJPLILFLR2ZYY2QM","download_json":"https://pith.science/pith/NEIO3OTBHJGJPLILFLR2ZYY2QM.json","view_paper":"https://pith.science/paper/NEIO3OTB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.15391&json=true","fetch_graph":"https://pith.science/api/pith-number/NEIO3OTBHJGJPLILFLR2ZYY2QM/graph.json","fetch_events":"https://pith.science/api/pith-number/NEIO3OTBHJGJPLILFLR2ZYY2QM/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NEIO3OTBHJGJPLILFLR2ZYY2QM/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NEIO3OTBHJGJPLILFLR2ZYY2QM/action/storage_attestation","attest_author":"https://pith.science/pith/NEIO3OTBHJGJPLILFLR2ZYY2QM/action/author_attestation","sign_citation":"https://pith.science/pith/NEIO3OTBHJGJPLILFLR2ZYY2QM/action/citation_signature","submit_replication":"https://pith.science/pith/NEIO3OTBHJGJPLILFLR2ZYY2QM/action/replication_record"}},"created_at":"2026-07-05T11:06:44.626417+00:00","updated_at":"2026-07-05T11:06:44.626417+00:00"}