{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:J4UOWDCGOTQWWQLRJQNO37FXG5","short_pith_number":"pith:J4UOWDCG","schema_version":"1.0","canonical_sha256":"4f28eb0c4674e16b41714c1aedfcb73779b8c8bb06cfbc4ae318472f2c814bca","source":{"kind":"arxiv","id":"2606.22741","version":1},"attestation_state":"computed","paper":{"title":"GRADE: Graph Representation of LLM Agent Dependency and Execution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Yue Zhao","submitted_at":"2026-06-22T01:03:21Z","abstract_excerpt":"Can one graph represent every kind of LLM agent's run? A trace records what each step did, never what it relied on, the state it read, and the results it reused. GRADE recovers that missing layer: it models any run as one graph over its step nodes with two edge layers, execution edges (what ran in what order) read from the trace for free, and dependency edges (what each step relied on) rarely logged, so each is graded by how it is known, observed, declared, or inferred. One representation, and each layer earns its place. Across six corpora of LLM agents spanning tool use, coding, and the web, "},"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":"2606.22741","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-22T01:03:21Z","cross_cats_sorted":[],"title_canon_sha256":"b95e73f8fad8b55fa69fbd218a3aa51920b59ed41c86711562646b55b7421b5d","abstract_canon_sha256":"583edde09abc21479c6e960c07478240bbf7b769f9987d26fb7a8599b447b167"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T02:13:46.058373Z","signature_b64":"jZAgIQxjaXTyPlgdZYZsAFimkc9p7YQfTK7StKjmR45lxMslE8SEdVTbyL9aDoG2m7bwLa0Taw9opj7CmMJtBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4f28eb0c4674e16b41714c1aedfcb73779b8c8bb06cfbc4ae318472f2c814bca","last_reissued_at":"2026-06-23T02:13:46.058027Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T02:13:46.058027Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GRADE: Graph Representation of LLM Agent Dependency and Execution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Yue Zhao","submitted_at":"2026-06-22T01:03:21Z","abstract_excerpt":"Can one graph represent every kind of LLM agent's run? A trace records what each step did, never what it relied on, the state it read, and the results it reused. GRADE recovers that missing layer: it models any run as one graph over its step nodes with two edge layers, execution edges (what ran in what order) read from the trace for free, and dependency edges (what each step relied on) rarely logged, so each is graded by how it is known, observed, declared, or inferred. One representation, and each layer earns its place. Across six corpora of LLM agents spanning tool use, coding, and the web, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.22741","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/2606.22741/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":"2606.22741","created_at":"2026-06-23T02:13:46.058086+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.22741v1","created_at":"2026-06-23T02:13:46.058086+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.22741","created_at":"2026-06-23T02:13:46.058086+00:00"},{"alias_kind":"pith_short_12","alias_value":"J4UOWDCGOTQW","created_at":"2026-06-23T02:13:46.058086+00:00"},{"alias_kind":"pith_short_16","alias_value":"J4UOWDCGOTQWWQLR","created_at":"2026-06-23T02:13:46.058086+00:00"},{"alias_kind":"pith_short_8","alias_value":"J4UOWDCG","created_at":"2026-06-23T02:13:46.058086+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/J4UOWDCGOTQWWQLRJQNO37FXG5","json":"https://pith.science/pith/J4UOWDCGOTQWWQLRJQNO37FXG5.json","graph_json":"https://pith.science/api/pith-number/J4UOWDCGOTQWWQLRJQNO37FXG5/graph.json","events_json":"https://pith.science/api/pith-number/J4UOWDCGOTQWWQLRJQNO37FXG5/events.json","paper":"https://pith.science/paper/J4UOWDCG"},"agent_actions":{"view_html":"https://pith.science/pith/J4UOWDCGOTQWWQLRJQNO37FXG5","download_json":"https://pith.science/pith/J4UOWDCGOTQWWQLRJQNO37FXG5.json","view_paper":"https://pith.science/paper/J4UOWDCG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.22741&json=true","fetch_graph":"https://pith.science/api/pith-number/J4UOWDCGOTQWWQLRJQNO37FXG5/graph.json","fetch_events":"https://pith.science/api/pith-number/J4UOWDCGOTQWWQLRJQNO37FXG5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J4UOWDCGOTQWWQLRJQNO37FXG5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J4UOWDCGOTQWWQLRJQNO37FXG5/action/storage_attestation","attest_author":"https://pith.science/pith/J4UOWDCGOTQWWQLRJQNO37FXG5/action/author_attestation","sign_citation":"https://pith.science/pith/J4UOWDCGOTQWWQLRJQNO37FXG5/action/citation_signature","submit_replication":"https://pith.science/pith/J4UOWDCGOTQWWQLRJQNO37FXG5/action/replication_record"}},"created_at":"2026-06-23T02:13:46.058086+00:00","updated_at":"2026-06-23T02:13:46.058086+00:00"}