{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:HEUCNSXALLJ4O2AYX3SF4DEAYH","short_pith_number":"pith:HEUCNSXA","schema_version":"1.0","canonical_sha256":"392826cae05ad3c76818bee45e0c80c1d5cbe012b23293a2d65310e62ad7a9a6","source":{"kind":"arxiv","id":"2606.24689","version":1},"attestation_state":"computed","paper":{"title":"Automated Summarization of Software Documents: An LLM-based Multi-Agent Approach","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Davide Di Ruscio, Duc S. H. Nguyen, Juri Di Rocco, Minh T. Nguyen, Phuong T. Nguyen","submitted_at":"2026-06-23T15:18:17Z","abstract_excerpt":"Large Language Models (LLMs) and LLM-based Multi-Agent Systems (MAS) are revolutionizing software engineering (SE) by advancing automation, decision-making, and knowledge processing. Their recent application to SE tasks has already shown promising results. In this paper, we focus on summarization as a key application area. We present Metagente, an LLM-based MAS designed to generate concise and accurate summaries of software documentation. Metagente employs a Teacher-Student architecture where multiple LLM agents collaborate to enhance relevance and precision of produced summaries. An empirical"},"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":"2606.24689","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.SE","submitted_at":"2026-06-23T15:18:17Z","cross_cats_sorted":[],"title_canon_sha256":"e23cb3246bbd07805dc02aa96cf28346b3d0639790c18e8c64143177203e10c2","abstract_canon_sha256":"abe9660ae34a0c53c54565c10c53c73fe4a54f619271049e7b7b7b87fd76f9d9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-24T01:15:39.278651Z","signature_b64":"8mlFx2Gouwq07UTsqwMBBn9dnFs76XJ2X50aW8Hojffhx7jIsqfGKlfs5r7YDgWSdoECYzxkILEqrCPP2Z0QCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"392826cae05ad3c76818bee45e0c80c1d5cbe012b23293a2d65310e62ad7a9a6","last_reissued_at":"2026-06-24T01:15:39.278217Z","signature_status":"signed_v1","first_computed_at":"2026-06-24T01:15:39.278217Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Automated Summarization of Software Documents: An LLM-based Multi-Agent Approach","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Davide Di Ruscio, Duc S. H. Nguyen, Juri Di Rocco, Minh T. Nguyen, Phuong T. Nguyen","submitted_at":"2026-06-23T15:18:17Z","abstract_excerpt":"Large Language Models (LLMs) and LLM-based Multi-Agent Systems (MAS) are revolutionizing software engineering (SE) by advancing automation, decision-making, and knowledge processing. Their recent application to SE tasks has already shown promising results. In this paper, we focus on summarization as a key application area. We present Metagente, an LLM-based MAS designed to generate concise and accurate summaries of software documentation. Metagente employs a Teacher-Student architecture where multiple LLM agents collaborate to enhance relevance and precision of produced summaries. An empirical"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.24689","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/2606.24689/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":"2606.24689","created_at":"2026-06-24T01:15:39.278279+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.24689v1","created_at":"2026-06-24T01:15:39.278279+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.24689","created_at":"2026-06-24T01:15:39.278279+00:00"},{"alias_kind":"pith_short_12","alias_value":"HEUCNSXALLJ4","created_at":"2026-06-24T01:15:39.278279+00:00"},{"alias_kind":"pith_short_16","alias_value":"HEUCNSXALLJ4O2AY","created_at":"2026-06-24T01:15:39.278279+00:00"},{"alias_kind":"pith_short_8","alias_value":"HEUCNSXA","created_at":"2026-06-24T01:15:39.278279+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/HEUCNSXALLJ4O2AYX3SF4DEAYH","json":"https://pith.science/pith/HEUCNSXALLJ4O2AYX3SF4DEAYH.json","graph_json":"https://pith.science/api/pith-number/HEUCNSXALLJ4O2AYX3SF4DEAYH/graph.json","events_json":"https://pith.science/api/pith-number/HEUCNSXALLJ4O2AYX3SF4DEAYH/events.json","paper":"https://pith.science/paper/HEUCNSXA"},"agent_actions":{"view_html":"https://pith.science/pith/HEUCNSXALLJ4O2AYX3SF4DEAYH","download_json":"https://pith.science/pith/HEUCNSXALLJ4O2AYX3SF4DEAYH.json","view_paper":"https://pith.science/paper/HEUCNSXA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.24689&json=true","fetch_graph":"https://pith.science/api/pith-number/HEUCNSXALLJ4O2AYX3SF4DEAYH/graph.json","fetch_events":"https://pith.science/api/pith-number/HEUCNSXALLJ4O2AYX3SF4DEAYH/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HEUCNSXALLJ4O2AYX3SF4DEAYH/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HEUCNSXALLJ4O2AYX3SF4DEAYH/action/storage_attestation","attest_author":"https://pith.science/pith/HEUCNSXALLJ4O2AYX3SF4DEAYH/action/author_attestation","sign_citation":"https://pith.science/pith/HEUCNSXALLJ4O2AYX3SF4DEAYH/action/citation_signature","submit_replication":"https://pith.science/pith/HEUCNSXALLJ4O2AYX3SF4DEAYH/action/replication_record"}},"created_at":"2026-06-24T01:15:39.278279+00:00","updated_at":"2026-06-24T01:15:39.278279+00:00"}