{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:6DXGPIRZQFBQJ4HAOQAKPIIDMV","short_pith_number":"pith:6DXGPIRZ","schema_version":"1.0","canonical_sha256":"f0ee67a239814304f0e07400a7a103654b055c42c68e6e7410dac6ca75f16466","source":{"kind":"arxiv","id":"2506.10737","version":1},"attestation_state":"computed","paper":{"title":"TaxoAdapt: Aligning LLM-Based Multidimensional Taxonomy Construction to Evolving Research Corpora","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CL","authors_text":"Jiawei Han, Nan Zhang, Prasenjit Mitra, Priyanka Kargupta, Rui Zhang, Yunyi Zhang","submitted_at":"2025-06-12T14:26:28Z","abstract_excerpt":"The rapid evolution of scientific fields introduces challenges in organizing and retrieving scientific literature. While expert-curated taxonomies have traditionally addressed this need, the process is time-consuming and expensive. Furthermore, recent automatic taxonomy construction methods either (1) over-rely on a specific corpus, sacrificing generalizability, or (2) depend heavily on the general knowledge of large language models (LLMs) contained within their pre-training datasets, often overlooking the dynamic nature of evolving scientific domains. Additionally, these approaches fail to ac"},"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":"2506.10737","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-12T14:26:28Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"4bb8a8659a2e225a2faf00da9e105fe1ec08dae8c04f1258415fa1b73fb6429e","abstract_canon_sha256":"181e44850c39a3f7c483300cf960b941fc35e8907a6a253f35098d8ccc9445ab"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:20:29.289670Z","signature_b64":"smrel5M6LXbKx1+9Zrs32ifmQ6wgz28F11X8Mi6jdnZ5G1AFfpjWEP0LOA0hszoAB7pgfY5OKgdgcD9u9ULQBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f0ee67a239814304f0e07400a7a103654b055c42c68e6e7410dac6ca75f16466","last_reissued_at":"2026-07-05T11:20:29.289183Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:20:29.289183Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"TaxoAdapt: Aligning LLM-Based Multidimensional Taxonomy Construction to Evolving Research Corpora","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CL","authors_text":"Jiawei Han, Nan Zhang, Prasenjit Mitra, Priyanka Kargupta, Rui Zhang, Yunyi Zhang","submitted_at":"2025-06-12T14:26:28Z","abstract_excerpt":"The rapid evolution of scientific fields introduces challenges in organizing and retrieving scientific literature. While expert-curated taxonomies have traditionally addressed this need, the process is time-consuming and expensive. Furthermore, recent automatic taxonomy construction methods either (1) over-rely on a specific corpus, sacrificing generalizability, or (2) depend heavily on the general knowledge of large language models (LLMs) contained within their pre-training datasets, often overlooking the dynamic nature of evolving scientific domains. Additionally, these approaches fail to ac"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.10737","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/2506.10737/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":"2506.10737","created_at":"2026-07-05T11:20:29.289246+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.10737v1","created_at":"2026-07-05T11:20:29.289246+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.10737","created_at":"2026-07-05T11:20:29.289246+00:00"},{"alias_kind":"pith_short_12","alias_value":"6DXGPIRZQFBQ","created_at":"2026-07-05T11:20:29.289246+00:00"},{"alias_kind":"pith_short_16","alias_value":"6DXGPIRZQFBQJ4HA","created_at":"2026-07-05T11:20:29.289246+00:00"},{"alias_kind":"pith_short_8","alias_value":"6DXGPIRZ","created_at":"2026-07-05T11:20:29.289246+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/6DXGPIRZQFBQJ4HAOQAKPIIDMV","json":"https://pith.science/pith/6DXGPIRZQFBQJ4HAOQAKPIIDMV.json","graph_json":"https://pith.science/api/pith-number/6DXGPIRZQFBQJ4HAOQAKPIIDMV/graph.json","events_json":"https://pith.science/api/pith-number/6DXGPIRZQFBQJ4HAOQAKPIIDMV/events.json","paper":"https://pith.science/paper/6DXGPIRZ"},"agent_actions":{"view_html":"https://pith.science/pith/6DXGPIRZQFBQJ4HAOQAKPIIDMV","download_json":"https://pith.science/pith/6DXGPIRZQFBQJ4HAOQAKPIIDMV.json","view_paper":"https://pith.science/paper/6DXGPIRZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.10737&json=true","fetch_graph":"https://pith.science/api/pith-number/6DXGPIRZQFBQJ4HAOQAKPIIDMV/graph.json","fetch_events":"https://pith.science/api/pith-number/6DXGPIRZQFBQJ4HAOQAKPIIDMV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6DXGPIRZQFBQJ4HAOQAKPIIDMV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6DXGPIRZQFBQJ4HAOQAKPIIDMV/action/storage_attestation","attest_author":"https://pith.science/pith/6DXGPIRZQFBQJ4HAOQAKPIIDMV/action/author_attestation","sign_citation":"https://pith.science/pith/6DXGPIRZQFBQJ4HAOQAKPIIDMV/action/citation_signature","submit_replication":"https://pith.science/pith/6DXGPIRZQFBQJ4HAOQAKPIIDMV/action/replication_record"}},"created_at":"2026-07-05T11:20:29.289246+00:00","updated_at":"2026-07-05T11:20:29.289246+00:00"}