{"_canonicalization":{"envelope_id":"axm_ + sha256(envelope minus {signature, axiom_id, anchors})","envelope_signature":"ed25519(envelope minus {signature, axiom_id})","json":"sort_keys=True, separators=(',',':'), ensure_ascii=False, allow_nan=False, utf-8","leaf_hash":"sha256(0x00 || canonical_json(envelope_full))","seal_signature":"ed25519(seal minus {signature, sig_algorithm})"},"axiom_id":"axm_136822d0efca54b1dc2be087f8d473b65dd76b6041824133ca2211fa188ae7ee","bitcoin_anchor":{"bitcoin_attestations":[],"calendar_attestations":[],"ots_url":"","stamped_at":"","status":"pending_next_stamp"},"envelope":{"anchors":[{"chain":"crovia.axiom_graph","height":0,"merkle_proof":"spider_vendor_press_v1","root_at_anchor":"spider_vendor_press_v1"}],"axiom_id":"axm_136822d0efca54b1dc2be087f8d473b65dd76b6041824133ca2211fa188ae7ee","axiom_type":"AX.OBS","body":{"axiom_subtype":"news.vendor_press.v1","category":"news","fingerprint":"5358e4f352ae569ef2a25944d31ddca3bc808c8ccd940abf2de128b1d68a2226","published":"Thu, 18 Jun 2026 00:00:00 -0400","receipt_hash":"5358e4f352ae569ef2a25944d31ddca3bc808c8ccd940abf2de128b1d68a2226","schema":"spider.news.vendor_press.v1","spider":"vendor_press","spider_record":{"axiom_subtype":"news.vendor_press.v1","category":"news","decision_hint":"POSITIVE","envelope_target":"AX.OBS","fingerprint":"5358e4f352ae569ef2a25944d31ddca3bc808c8ccd940abf2de128b1d68a2226","observed_at":"2026-06-18T04:43:37.219665Z","parent_run_hash":"de79a40f7b3537d88842f7ac355e799c5df2adcb4fc32a4e28096d4bbdf01739","published":"Thu, 18 Jun 2026 00:00:00 -0400","runtime_version":"0.1.0","schema":"spider.news.vendor_press.v1","source_status":200,"source_url":"https://export.arxiv.org/rss/cs.AI","spider":"vendor_press","summary_excerpt":"arXiv:2605.26903v2 Announce Type: replace-cross \nAbstract: Structured data is well handled by gradient-boosted decision trees (GBDT), which are usually trained on vertically partitioned features across mutually distrustful parties. High speed and interpretability make GBDTs popular in finance and healthcare, where neural networks may fall short. Enabling secure computation for GBDTs poses unique challenges, requiring secure record alignment for comparison. Relying on private set intersection (PSI) is a de facto approach. Mistaking PSI for a safety measure actually exposes which record identifiers (IDs) are shared between the datasets. Although circuit-PSI could help, it is costly for generic uses. New ideas are needed to efficiently train in a \"dark forest\". Aiming to hide the IDs, we initiate the study of anonymous GBDT training on split data held by two parties. Dual circuit-PSI in our design lets the parties alternate as receiver to run pick-then-sum over local features. Via oblivio","title":"Practical Anonymous Two-Party Gradient Boosting Decision Tree","url":"https://arxiv.org/abs/2605.26903","vendor":"arxiv_cs_ai"},"summary":"arXiv:2605.26903v2 Announce Type: replace-cross \nAbstract: Structured data is well handled by gradient-boosted decision trees (GBDT), which are usually trained on vertically partitioned features across mutually distrustful parties. High speed and interpretability make GBDTs popular in finance and healthcare, where neural networks may fall short. Enabling secure computation for GBDTs poses unique challenges, requiring secure record alignment for comparison. Relying on private set intersection (PSI) is a de facto approach. Mistaking PSI for a safety measure actually exposes which record identifiers (IDs) are shared between the datasets. Although circuit-PSI could help, it is costly for generic uses. New ideas are needed to efficiently train in a \"dark forest\". Aiming to hide the IDs, we initiate the study of anonymous GBDT training on split data held by two parties. Dual circuit-PSI in our design lets the parties alternate as receiver to run pick-then-sum over local features. Via oblivio","title":"Practical Anonymous Two-Party Gradient Boosting Decision Tree","vendor":"arxiv_cs_ai"},"confidence":{"method":"deterministic"},"decision":"POSITIVE","issued_at":"2026-06-18T04:43:37Z","notes":"Spider vendor_press (news) news.vendor_press.v1","object":{"captured_by":"crovia.spider.vendor_press","primary_source_url":"https://arxiv.org/abs/2605.26903"},"predecessors":[],"schema":"crovia.axiom.v1","signature":"ed25519:12bc6202740d954ca902165542ee4baec08a6c7b5d44d03851e039a2fb134ccdd6ab22553ac79fc8ec3e9e310cb2c470e093dd42ac6812918d1a36018235ef08","signer":"crovia.substrate","subject":{"observed_at":"2026-06-18T04:43:37Z","source_collector":"spider:vendor_press","target_id":"https://arxiv.org/abs/2605.26903"},"tsa":{"authority":"crovia.substrate.bootstrap","rfc3161_token":"{\"kind\":\"crovia.bootstrap.tsa\",\"source_jsonl\":\"/opt/crovia/spider/data/news/vendor_press_v1.jsonl\",\"source_seal_merkle_root\":\"spider_vendor_press_v1\",\"upgrade_path\":\"Sessione H \\u2014 OpenTimestamps weekly anchor\"}"},"zk_mode":"clear","zk_proof":null},"ledger":{"leaf_hash":"8271d45aaf69b04d0faf6944ae0fd191f8d5f2432be1ecaf4d0b55c653834ba4","leaf_index":233517,"ledger_path":"/opt/crovia/substrate/axiom_ledger.jsonl"},"merkle_proof":{"hash_alg":"sha256","leaf_prefix":"0x00","node_prefix":"0x01","odd_leaf_rule":"duplicate_last","path":[{"sibling":"5a68d96c756a31c1ccfb66eb83d24e91e3fba610721adb5b90c9fcf8c39e6024","side":"left"},{"sibling":"49842f172cdbb018b294ab8b3530a93a406c8b2d06a509624a4a928fcea874ba","side":"right"},{"sibling":"e54afe37a0c82e1207519ee31a7fe7526952463e20d6a5f4636193f48f8471a1","side":"left"},{"sibling":"7a36ba770b4a56ac1a910ee3f4a605169ed9407d7ec9f461d5be2a5d5704a413","side":"left"},{"sibling":"ccef570cc5460ba72a01b2a0b3b6e7eee19dfe0476c303523c1d0b6d5e6c19ba","side":"right"},{"sibling":"c42f991fcbafbe53d8fc33e1c5c2d1d51ef70e0c2709828f03f40cba8d7b8389","side":"left"},{"sibling":"5e436eec5370aaf4cccb6c432bd004f0a554eab0e19ec87f70ba66470ad7303b","side":"right"},{"sibling":"fe9c643bdeb268143f61f15d89d0ff9dd03becb2914656c7a873d95f7266b5ce","side":"right"},{"sibling":"ad9e1cf26277141407aebd8692bfb16135dd1e614913e54b1dd445fed15d105a","side":"right"},{"sibling":"b151db1a7de0ce9a329250fae8b690f5b55ab3cfe5468a1fbb5f5bde0703b420","side":"right"},{"sibling":"7dc9143c057343b46a3b988492fba5262dec443cc1fb6070e3ea81543ca6a522","side":"right"},{"sibling":"ad5850946feb9a22361b5b9df0884f9ef1edcc7efea0374ff5782080ccb1a947","side":"right"},{"sibling":"410c633928fea11c5b4bdddb431956b1d7c320db9cda00d2fe32e0fcf888d7b7","side":"left"},{"sibling":"e616c34dbaf9456d5a6d3e2da82cde8621293c9f6d8a4cf9e441d7fd9cc81579","side":"right"},{"sibling":"94c0c932e61657f5e37fdba43f6ca9eddea8359425a7c1558dabe566911d5304","side":"right"},{"sibling":"a04392fb9f2a3a620840e3b3fecd93d12e6d224e481c162389d8ae64e7194599","side":"left"},{"sibling":"c300cf0154c136afc09b1702a0be98f4ba5b6dc5cf57e8cc714ec1eaf4196eff","side":"left"},{"sibling":"d841ad93efda0869e5eb97678f348f03f5caab4353e05ff4bf18f47fb945b822","side":"left"}]},"schema":"crovia.axiom_proof.v1","seal":{"first_collector_run_id":"","first_receipt_hash":"","jsonl_path":"/opt/crovia/substrate/axiom_ledger.jsonl","key_id":"430895f101d38164","last_collector_run_id":"","last_receipt_hash":"","leaf_count":234491,"merkle_root":"02576a6980e38bab47864ae2c57b5a5ff21e554e9bdf8f64bdf28155ff1aabec","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","run_id":"hourly_json_retrofit_20260618T143732Z","schema":"crovia.seal.v1","seal_family_version":"crovia-seal-family/1","seal_kind":"substrate_batch","sealed_at":"2026-06-18T18:33:39Z","sig_algorithm":"ed25519","signature":"b6c708778fc38b7789a2b91156cfe87252a7cd3a1d29121cba11a0c78f8cf104ca3019fc50a962fa5a216bcc4922fc8f3f69c04d1f8332c6dc0d931e1012e502","signer_version":"1.1.0"},"trust_root":{"key_id":"430895f101d38164","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","signature_algorithm":"ed25519","url":"/registry/canon/TRUST_ROOT.md"},"verifier":{"spec":"/registry/canon/AXIOM_RECEIPT_v1.md","url":"/v/axm_136822d0efca54b1dc2be087f8d473b65dd76b6041824133ca2211fa188ae7ee"}}