{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VVZ66YJL5S2JCQDEEYBYHRPNN5","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":"c5705470046fb7d98d4f750e9b0a4b6b4a81e3ce153211fbb93a7da501000782","cross_cats_sorted":["cs.CL","cs.MA"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-14T03:26:43Z","title_canon_sha256":"155a71065b6a2681e76b33f78d88f0f2a471772a3f26996dcffe46e4c3e46fe9"},"schema_version":"1.0","source":{"id":"2501.07815","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.07815","created_at":"2026-07-05T10:00:50Z"},{"alias_kind":"arxiv_version","alias_value":"2501.07815v1","created_at":"2026-07-05T10:00:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.07815","created_at":"2026-07-05T10:00:50Z"},{"alias_kind":"pith_short_12","alias_value":"VVZ66YJL5S2J","created_at":"2026-07-05T10:00:50Z"},{"alias_kind":"pith_short_16","alias_value":"VVZ66YJL5S2JCQDE","created_at":"2026-07-05T10:00:50Z"},{"alias_kind":"pith_short_8","alias_value":"VVZ66YJL","created_at":"2026-07-05T10:00:50Z"}],"graph_snapshots":[{"event_id":"sha256:fa2955b5775f2a0cca92752dbc05b6a0ad6a8da4ff79d7b6221238e84a47ddeb","target":"graph","created_at":"2026-07-05T10:00:50Z","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/2501.07815/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advances in prompting techniques and multi-agent systems for Large Language Models (LLMs) have produced increasingly complex approaches. However, we lack a framework for characterizing and comparing prompting techniques or understanding their relationship to multi-agent LLM systems. This position paper introduces and explains the concepts of linear contexts (a single, continuous sequence of interactions) and non-linear contexts (branching or multi-path) in LLM systems. These concepts enable the development of an agent-centric projection of prompting techniques, a framework that can reve","authors_text":"Dhruv Dhamani, Mary Lou Maher","cross_cats":["cs.CL","cs.MA"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-14T03:26:43Z","title":"Agent-Centric Projection of Prompting Techniques and Implications for Synthetic Training Data for Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.07815","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":"sha256:97e297951399853a73620d2769dd241bc6eb750cfec079c8a914035c65e87456","target":"record","created_at":"2026-07-05T10:00:50Z","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":"c5705470046fb7d98d4f750e9b0a4b6b4a81e3ce153211fbb93a7da501000782","cross_cats_sorted":["cs.CL","cs.MA"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-14T03:26:43Z","title_canon_sha256":"155a71065b6a2681e76b33f78d88f0f2a471772a3f26996dcffe46e4c3e46fe9"},"schema_version":"1.0","source":{"id":"2501.07815","kind":"arxiv","version":1}},"canonical_sha256":"ad73ef612becb4914064260383c5ed6f6c86e66d5302dfaa2a2e73fac20e8d98","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ad73ef612becb4914064260383c5ed6f6c86e66d5302dfaa2a2e73fac20e8d98","first_computed_at":"2026-07-05T10:00:50.568666Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:00:50.568666Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EKO4Zd2OHt5soyblemg6gB+/1+Wh5OS+x5kBOU+dUZMveI97KlMDoJemEccXytGYqU11Hby5fMg4pT4+HstrDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:00:50.569205Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.07815","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:97e297951399853a73620d2769dd241bc6eb750cfec079c8a914035c65e87456","sha256:fa2955b5775f2a0cca92752dbc05b6a0ad6a8da4ff79d7b6221238e84a47ddeb"],"state_sha256":"c815b29338ad176e9b2575b5673a893a575d2cb7bf3c1ad589058ec6d3bc4418"}