{"_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_1f2950899a5496892ebe25c67015ade510815b3c8d39e8761c6e5c6b7b5d8516","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_1f2950899a5496892ebe25c67015ade510815b3c8d39e8761c6e5c6b7b5d8516","axiom_type":"AX.OBS","body":{"axiom_subtype":"news.vendor_press.v1","category":"news","fingerprint":"9d1de2edcb6d1af38cea555139b67386a20601a613a94d37c72c9f8af0ceb3d2","published":"Fri, 19 Jun 2026 00:00:00 -0400","receipt_hash":"9d1de2edcb6d1af38cea555139b67386a20601a613a94d37c72c9f8af0ceb3d2","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":"9d1de2edcb6d1af38cea555139b67386a20601a613a94d37c72c9f8af0ceb3d2","observed_at":"2026-06-19T04:43:39.497162Z","parent_run_hash":"942f204649bd8fb7e5f3ac68f64dc64a5a02624b49ac200c0f629f6ff3a211f3","published":"Fri, 19 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:2606.19588v1 Announce Type: new \nAbstract: Formal tools such as SAT and SMT solvers are increasingly embedded in language model reasoning pipelines when a safety or security critical question can be formulated in logic. Unlike chain of thought whose steps are sampled from the model distribution without formal guarantee, a solver produces a sound and independently verifiable answer. However, the soundness guarantee can be lost in the interaction between the solver and the model. The hybrid pipeline has three components: formalizing the question, deciding it, and narrating the result. Prior work has studied the formalization and decision, but not narration, which is the step that turns a formal tool's output into the user answer. To fill the narration gap, we first model the LLM-solver loop as a verified decision procedure. We further evaluate five open-sourced models under prompt injection, and we find certificate gating makes the solver verdict sound, while an adversary can inver","title":"Analyzing the Narration Gap in LLM-Solver Loops","url":"https://arxiv.org/abs/2606.19588","vendor":"arxiv_cs_ai"},"summary":"arXiv:2606.19588v1 Announce Type: new \nAbstract: Formal tools such as SAT and SMT solvers are increasingly embedded in language model reasoning pipelines when a safety or security critical question can be formulated in logic. Unlike chain of thought whose steps are sampled from the model distribution without formal guarantee, a solver produces a sound and independently verifiable answer. However, the soundness guarantee can be lost in the interaction between the solver and the model. The hybrid pipeline has three components: formalizing the question, deciding it, and narrating the result. Prior work has studied the formalization and decision, but not narration, which is the step that turns a formal tool's output into the user answer. To fill the narration gap, we first model the LLM-solver loop as a verified decision procedure. We further evaluate five open-sourced models under prompt injection, and we find certificate gating makes the solver verdict sound, while an adversary can inver","title":"Analyzing the Narration Gap in LLM-Solver Loops","vendor":"arxiv_cs_ai"},"confidence":{"method":"deterministic"},"decision":"POSITIVE","issued_at":"2026-06-19T04:43:39Z","notes":"Spider vendor_press (news) news.vendor_press.v1","object":{"captured_by":"crovia.spider.vendor_press","primary_source_url":"https://arxiv.org/abs/2606.19588"},"predecessors":[],"schema":"crovia.axiom.v1","signature":"ed25519:f8d1d73fb21cfd0874e65c2214b993e2ce965afd760bf8915912378d580adb6f88a2f9e53fccb8983bc5c1a80133c1000bbae8fd5dd3a93e30a63aae42251d0a","signer":"crovia.substrate","subject":{"observed_at":"2026-06-19T04:43:39Z","source_collector":"spider:vendor_press","target_id":"https://arxiv.org/abs/2606.19588"},"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":"a146d0d02f11725a68c23a3474996d244628a61f9d712404296794d4a69121dc","leaf_index":235466,"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":"8b39fff58af73a3a82ad7dfa7da6d4c4174b483087e93455f573f23fb9797cdb","side":"right"},{"sibling":"4915152ee7946d079e52e2c4ccb1e6d3c6b138f4e3647428f4d8f6ae288567c2","side":"left"},{"sibling":"f34524baf536cb76da80fdf418d956c08991be7da978e040802ae6de1586a859","side":"right"},{"sibling":"0c8ffb410affcb1ee44c49284e55c8bd7f4c5b25534e35fd3839a1815612e274","side":"left"},{"sibling":"03fc56070f0c5089bf6ede33ae0559da5ff3b395217f6cae545f79f7e34fc505","side":"right"},{"sibling":"bcc64a96b2351ef6571992656cd86c436090f98a58edd222113a9eab3bbe6e32","side":"right"},{"sibling":"696ac6bcf68966ee959b35539f0bed60b3216ccb53620defd29feb8dbcb2ac30","side":"left"},{"sibling":"95ba45f2fea2d822bc863962b7e478ea50086827d90fab88c0da065d454d7ac5","side":"left"},{"sibling":"00f27f149ddd2eb0d2cf60eaed9e1d55c662cf1cf69c95fbea03bba9d35f90c7","side":"left"},{"sibling":"797e0feb6bf826a55956c876711cd24824818c5a84a591f8cc06b95577b3405d","side":"left"},{"sibling":"f049d6e86b410f6f63921a6e3aa684efffa398fd23eed28245c43b156d404c5f","side":"left"},{"sibling":"9ec7f4f84de7e2057a02ac55686567b21acfd5beaecc7a84e9e48f3db17296c2","side":"right"},{"sibling":"410c633928fea11c5b4bdddb431956b1d7c320db9cda00d2fe32e0fcf888d7b7","side":"left"},{"sibling":"b52a771530dd1686bca49e42088898b86da94879579cd6a995c6ab0598a665fe","side":"right"},{"sibling":"a116bb92f9b0350491155b470acc86d006c33ec558759e49e56614a54c39f242","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":241122,"merkle_root":"7a906c6a26ff6c6feabc2feaba6a1a70c515e6fd72a38c779293b0f78ff291c4","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","run_id":"hourly_json_retrofit_20260622T183701Z","schema":"crovia.seal.v1","seal_family_version":"crovia-seal-family/1","seal_kind":"substrate_batch","sealed_at":"2026-06-23T06:25:25Z","sig_algorithm":"ed25519","signature":"5576b1d56d5dbb0d96c780fa3ca0940d805c8de95c6251bc87297f0be058aa5e37eb53a6aa1b601381f489f093842cf674b28737ed8e46ce3a49814b5e57290c","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_1f2950899a5496892ebe25c67015ade510815b3c8d39e8761c6e5c6b7b5d8516"}}