{"_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_120dfafdfc0dff1c9da3c0292febb02a5adfcdae64f9cf432241f1b25e097d1b","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_120dfafdfc0dff1c9da3c0292febb02a5adfcdae64f9cf432241f1b25e097d1b","axiom_type":"AX.OBS","body":{"axiom_subtype":"news.vendor_press.v1","category":"news","fingerprint":"17cd94090d10914ee9c0df96db695268675770c06b37130c2378147d80544cdf","published":"Tue, 07 Jul 2026 00:00:00 -0400","receipt_hash":"17cd94090d10914ee9c0df96db695268675770c06b37130c2378147d80544cdf","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":"17cd94090d10914ee9c0df96db695268675770c06b37130c2378147d80544cdf","observed_at":"2026-07-07T04:43:08.294902Z","parent_run_hash":"fc40a96e5d33ecc82922806c3ad18de4725d7af03964570396c8af4e48fb5bc1","published":"Tue, 07 Jul 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:2607.02975v1 Announce Type: new \nAbstract: Effective agency in social environments depends on when an agent seeks knowledge, when it acts, and whether its actions are justified by acquired information. Existing grounded benchmarks provide executable actions, persistent state, and verifiable outcomes, while social simulation environments provide rich interaction among language agents. We study an evaluation setting that combines these requirements. We define socially distributed task environments as interactive environments where task-relevant knowledge is partitioned across role-isolated participants and consequential actions are accessible only through them. Communication serves as exploration over role-partitioned knowledge, while grounded action serves as exploitation over environment state. We introduce Incognita, a Concordia-based framework that separates social interaction from grounded execution. The evaluated agent routes messages to a user or specialist entities; special","title":"Evaluating Generative Agents with Actions Grounded in Socially Distributed Task Environments using Incognita","url":"https://arxiv.org/abs/2607.02975","vendor":"arxiv_cs_ai"},"summary":"arXiv:2607.02975v1 Announce Type: new \nAbstract: Effective agency in social environments depends on when an agent seeks knowledge, when it acts, and whether its actions are justified by acquired information. Existing grounded benchmarks provide executable actions, persistent state, and verifiable outcomes, while social simulation environments provide rich interaction among language agents. We study an evaluation setting that combines these requirements. We define socially distributed task environments as interactive environments where task-relevant knowledge is partitioned across role-isolated participants and consequential actions are accessible only through them. Communication serves as exploration over role-partitioned knowledge, while grounded action serves as exploitation over environment state. We introduce Incognita, a Concordia-based framework that separates social interaction from grounded execution. The evaluated agent routes messages to a user or specialist entities; special","title":"Evaluating Generative Agents with Actions Grounded in Socially Distributed Task Environments using Incognita","vendor":"arxiv_cs_ai"},"confidence":{"method":"deterministic"},"decision":"POSITIVE","issued_at":"2026-07-07T04:43:08Z","notes":"Spider vendor_press (news) news.vendor_press.v1","object":{"captured_by":"crovia.spider.vendor_press","primary_source_url":"https://arxiv.org/abs/2607.02975"},"predecessors":[],"schema":"crovia.axiom.v1","signature":"ed25519:e8adc78042d27254cce73894e9f6bb1af77d00e5b7e3162fb2f5f50804feed51d52f4e1499063cfe89a63dc77fcba53004c81736e01fbe2e1472786c9a9db208","signer":"crovia.substrate","subject":{"observed_at":"2026-07-07T04:43:08Z","source_collector":"spider:vendor_press","target_id":"https://arxiv.org/abs/2607.02975"},"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":"ba11fe6662e0fb3c1fc305bbba14f8eb80cf1b5023417771a51b6f6a6e8b1592","leaf_index":288721,"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":"0c66bccd9b2f096ba322d37dac548e6dcb4d3545be350bd944dd4ba486b9d654","side":"left"},{"sibling":"baf50e040234123c267fe42f13b0d06b8ec03cf34ff3ed314fc5278e660e8855","side":"right"},{"sibling":"14325f846fa0669f9e59c42e8dcb73dd3e9a6c14b1974f24886977a524c34be5","side":"right"},{"sibling":"920e39a4ffc504341dcb758e1981cd32bdb0cef664858c2852775e64d248a58f","side":"right"},{"sibling":"31347ca06a4774b8956440f8193fa1632894bf12e556e7082239a53fb87cd6ce","side":"left"},{"sibling":"c76dc76bc3b8846cbe60652cbb6f294981e01febd0141a65773df572e2064658","side":"right"},{"sibling":"61f7272108de819a7a77493153b988651785961143dd7f7cbf21c3d662725b0d","side":"left"},{"sibling":"693d22f9477576140ca2120520ac7b4b633fb122e7f590d3abc01e28b77f9cfe","side":"left"},{"sibling":"2b24ae0b0e86a6bb85711be0b56eabcfea8026b8cad7364829595d5562ea5b79","side":"left"},{"sibling":"66acb8614a0400fe91b4430bfa4ca8f7f359fb95aea361dfea6a7c88a9fe24a7","side":"left"},{"sibling":"b76af82f0e95812185e25016354f4707e41c1bacfe819e4948e5e364745511e8","side":"left"},{"sibling":"175b61fd9088baa970ad449ad7fc5d7babb21d38120cfa8c28053ae9d448ac83","side":"right"},{"sibling":"aae716235efcb893a1f219dbcd5095070d08a497769fc6d50c14976aa26d5750","side":"right"},{"sibling":"a75ab4319e241beeddb1b3f5705febe0422937926c3479923ccfb0b0082fa4e3","side":"left"},{"sibling":"bd04fa605f883bfb2b81510d045b1e85e555a03da3be083619f61384dfe40ff8","side":"left"},{"sibling":"1b72ad8d12164fdf329e7871711be99d8569d140b21f94056e6962da21da9ce1","side":"right"},{"sibling":"5f5109c2bfdcc7a7e70554bba25862e2d7ce86b6b0cd48a72eb66d2eb735f321","side":"right"},{"sibling":"05fd8a05dddb2e7f72bbb5b290ca55c378f1aed709f132277908d9a5f30eb605","side":"right"},{"sibling":"1cecb7f447febd025aac272837c80de218aecc6485d2395a509b2a1f1b9c746e","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":289613,"merkle_root":"dc428b9d9ba248d4f93f63147bf7c700bf5be7f500cec6c3507b9df6e9401601","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","run_id":"hourly_json_retrofit_20260707T053701Z","schema":"crovia.seal.v1","seal_family_version":"crovia-seal-family/1","seal_kind":"substrate_batch","sealed_at":"2026-07-07T05:38:15Z","sig_algorithm":"ed25519","signature":"c468b0e183383ab71992be40bda451093e6cd8cd8efb0d26f68e135a804b287c209d12a0f4fdd95c69c835c04b78df8cb1903dee1f53d4730b36f5332a29fe05","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_120dfafdfc0dff1c9da3c0292febb02a5adfcdae64f9cf432241f1b25e097d1b"}}