{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:D7USVUNQ3DSIZHNQY62SG73PYN","short_pith_number":"pith:D7USVUNQ","schema_version":"1.0","canonical_sha256":"1fe92ad1b0d8e48c9db0c7b5237f6fc35e98eb56b4a1b66ab5eb4e25ac59ec54","source":{"kind":"arxiv","id":"2412.00722","version":1},"attestation_state":"computed","paper":{"title":"Towards Adaptive Mechanism Activation in Language Agent","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Jun Zhao, Kang Liu, Ziyang Huang","submitted_at":"2024-12-01T08:10:04Z","abstract_excerpt":"Language Agent could be endowed with different mechanisms for autonomous task accomplishment. Current agents typically rely on fixed mechanisms or a set of mechanisms activated in a predefined order, limiting their adaptation to varied potential task solution structures. To this end, this paper proposes \\textbf{A}daptive \\textbf{L}anguage \\textbf{A}gent \\textbf{M}echanism \\textbf{A}ctivation Learning with Self-Exploration (\\textbf{ALAMA}), which focuses on optimizing mechanism activation adaptability without reliance on expert models. Initially, it builds a harmonized agent framework (\\textbf{"},"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":"2412.00722","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-01T08:10:04Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dfd2ae96eef61b08ebcebb91b6e9c5dc2f6165e2ac8ba4383bc204dc65e6575c","abstract_canon_sha256":"9d8791743e498bf63f9c93856aee60c9b9beaa7b1b15e077935ab3c9f76260be"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:42:46.160973Z","signature_b64":"J3bBWkHOZRhcRvoHTKtABaKUZ4LrpqUkPb20noGy88nM9b0ylgNGKeEhXlilQXB85LdkPVfpkhJyfV4lHjDUAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1fe92ad1b0d8e48c9db0c7b5237f6fc35e98eb56b4a1b66ab5eb4e25ac59ec54","last_reissued_at":"2026-07-05T09:42:46.160361Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:42:46.160361Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards Adaptive Mechanism Activation in Language Agent","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Jun Zhao, Kang Liu, Ziyang Huang","submitted_at":"2024-12-01T08:10:04Z","abstract_excerpt":"Language Agent could be endowed with different mechanisms for autonomous task accomplishment. Current agents typically rely on fixed mechanisms or a set of mechanisms activated in a predefined order, limiting their adaptation to varied potential task solution structures. To this end, this paper proposes \\textbf{A}daptive \\textbf{L}anguage \\textbf{A}gent \\textbf{M}echanism \\textbf{A}ctivation Learning with Self-Exploration (\\textbf{ALAMA}), which focuses on optimizing mechanism activation adaptability without reliance on expert models. Initially, it builds a harmonized agent framework (\\textbf{"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.00722","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/2412.00722/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":"2412.00722","created_at":"2026-07-05T09:42:46.160445+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.00722v1","created_at":"2026-07-05T09:42:46.160445+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.00722","created_at":"2026-07-05T09:42:46.160445+00:00"},{"alias_kind":"pith_short_12","alias_value":"D7USVUNQ3DSI","created_at":"2026-07-05T09:42:46.160445+00:00"},{"alias_kind":"pith_short_16","alias_value":"D7USVUNQ3DSIZHNQ","created_at":"2026-07-05T09:42:46.160445+00:00"},{"alias_kind":"pith_short_8","alias_value":"D7USVUNQ","created_at":"2026-07-05T09:42:46.160445+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/D7USVUNQ3DSIZHNQY62SG73PYN","json":"https://pith.science/pith/D7USVUNQ3DSIZHNQY62SG73PYN.json","graph_json":"https://pith.science/api/pith-number/D7USVUNQ3DSIZHNQY62SG73PYN/graph.json","events_json":"https://pith.science/api/pith-number/D7USVUNQ3DSIZHNQY62SG73PYN/events.json","paper":"https://pith.science/paper/D7USVUNQ"},"agent_actions":{"view_html":"https://pith.science/pith/D7USVUNQ3DSIZHNQY62SG73PYN","download_json":"https://pith.science/pith/D7USVUNQ3DSIZHNQY62SG73PYN.json","view_paper":"https://pith.science/paper/D7USVUNQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.00722&json=true","fetch_graph":"https://pith.science/api/pith-number/D7USVUNQ3DSIZHNQY62SG73PYN/graph.json","fetch_events":"https://pith.science/api/pith-number/D7USVUNQ3DSIZHNQY62SG73PYN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/D7USVUNQ3DSIZHNQY62SG73PYN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/D7USVUNQ3DSIZHNQY62SG73PYN/action/storage_attestation","attest_author":"https://pith.science/pith/D7USVUNQ3DSIZHNQY62SG73PYN/action/author_attestation","sign_citation":"https://pith.science/pith/D7USVUNQ3DSIZHNQY62SG73PYN/action/citation_signature","submit_replication":"https://pith.science/pith/D7USVUNQ3DSIZHNQY62SG73PYN/action/replication_record"}},"created_at":"2026-07-05T09:42:46.160445+00:00","updated_at":"2026-07-05T09:42:46.160445+00:00"}