{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:X3LNXZFC5G344BGJNK4DBZFXWI","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":"5cc9185b286f9772e13a01253eff865a19ee7acde8d6314d50c8eea6170bd4a9","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-11T13:48:25Z","title_canon_sha256":"bce08a0fc96106e5a3b94949a1e888c8737285b6cf7f523560bf047a998e6cad"},"schema_version":"1.0","source":{"id":"2506.09742","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.09742","created_at":"2026-07-05T11:19:56Z"},{"alias_kind":"arxiv_version","alias_value":"2506.09742v1","created_at":"2026-07-05T11:19:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.09742","created_at":"2026-07-05T11:19:56Z"},{"alias_kind":"pith_short_12","alias_value":"X3LNXZFC5G34","created_at":"2026-07-05T11:19:56Z"},{"alias_kind":"pith_short_16","alias_value":"X3LNXZFC5G344BGJ","created_at":"2026-07-05T11:19:56Z"},{"alias_kind":"pith_short_8","alias_value":"X3LNXZFC","created_at":"2026-07-05T11:19:56Z"}],"graph_snapshots":[{"event_id":"sha256:c9e30e9b58ffef7ea61a7a8f19be41a49ec8b8ca0c78c1b5127ee118409381c4","target":"graph","created_at":"2026-07-05T11:19:56Z","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/2506.09742/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Monitoring Machine Learning (ML) models in production environments is crucial, yet traditional approaches often yield verbose, low-interpretability outputs that hinder effective decision-making. We propose a cognitive architecture for ML monitoring that applies feature engineering principles to agents based on Large Language Models (LLMs), significantly enhancing the interpretability of monitoring outputs. Central to our approach is a Decision Procedure module that simulates feature engineering through three key steps: Refactor, Break Down, and Compile. The Refactor step improves data represen","authors_text":"Ajay Dholakia, David Ellison, Gusseppe Bravo-Rocca, Jordi Guitart, Peini Liu, Rodrigo M Carrillo-Larco","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-11T13:48:25Z","title":"Feature Engineering for Agents: An Adaptive Cognitive Architecture for Interpretable ML Monitoring"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.09742","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":"sha256:90fc13f8bdc0a60ffe04f436dca41ba8c812db49755fba9dcf49156766f91262","target":"record","created_at":"2026-07-05T11:19:56Z","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":"5cc9185b286f9772e13a01253eff865a19ee7acde8d6314d50c8eea6170bd4a9","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-11T13:48:25Z","title_canon_sha256":"bce08a0fc96106e5a3b94949a1e888c8737285b6cf7f523560bf047a998e6cad"},"schema_version":"1.0","source":{"id":"2506.09742","kind":"arxiv","version":1}},"canonical_sha256":"bed6dbe4a2e9b7ce04c96ab830e4b7b23c366409b509a53ce8ebcabcb1b5dac0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bed6dbe4a2e9b7ce04c96ab830e4b7b23c366409b509a53ce8ebcabcb1b5dac0","first_computed_at":"2026-07-05T11:19:56.219580Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:19:56.219580Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"53AFOEvghldJcz+RUEes1i0lpnDh/5PxssmEaPuPcpeXJvmf8QXTNsfQ5VpLrtKeZsScMxzTQ0Y4J/WsxDt8Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T11:19:56.220112Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.09742","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:90fc13f8bdc0a60ffe04f436dca41ba8c812db49755fba9dcf49156766f91262","sha256:c9e30e9b58ffef7ea61a7a8f19be41a49ec8b8ca0c78c1b5127ee118409381c4"],"state_sha256":"5b5adf8636f6aa9e5a6b66ed5989bbf592125e9d475a0db619b957a0ff09bc5a"}