{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:J3UFKIZ3KX2VN4DEPFRUDA43QG","short_pith_number":"pith:J3UFKIZ3","schema_version":"1.0","canonical_sha256":"4ee855233b55f556f064796341839b81bb078ec4972447e9568609bb0ffcf1ee","source":{"kind":"arxiv","id":"2504.02429","version":2},"attestation_state":"computed","paper":{"title":"MulFSA: Multi-level Financial Sentiment Analysis Framework for Bond Market","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CE","authors_text":"Junbo Wang, Lei Long, Ruiting Ma, Xin Li, Xuebin Chen, Yiwei Liu, Yuankai Wu","submitted_at":"2025-04-03T09:35:07Z","abstract_excerpt":"Existing financial sentiment analysis methods often fail to capture the multi-faceted nature of risk in bond markets due to their single-level approach and neglect of temporal dynamics. We propose Multi-level Financial Sentiment Analysis (MulFSA) based on pre-trained language models (PLMs) and large language models (LLMs), a novel framework that systematically integrates firm-specific micro-level sentiment, industry-specific meso-level sentiment, and duration-aware smoothing to model the latency and persistence of textual impact. Applying MulFSA to the comprehensive Chinese bond market corpus "},"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":"2504.02429","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CE","submitted_at":"2025-04-03T09:35:07Z","cross_cats_sorted":[],"title_canon_sha256":"b89ca0cb213c11911d73dc4d47f282a52f7c5a3211a143db2eb7e191211ae321","abstract_canon_sha256":"19d2dba741721782295a4e48fce3f6e911724b9e732868730f3a16a639290e56"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-21T01:05:05.243757Z","signature_b64":"yqWRXJ0w6S7VV+6Sgjl/NJpCQO9RQkPtcpEKPmurg2tKcr3MIhK3uwARDvBqx7mFVFLHJVFmHqWoF5bL5INIDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4ee855233b55f556f064796341839b81bb078ec4972447e9568609bb0ffcf1ee","last_reissued_at":"2026-05-21T01:05:05.242807Z","signature_status":"signed_v1","first_computed_at":"2026-05-21T01:05:05.242807Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MulFSA: Multi-level Financial Sentiment Analysis Framework for Bond Market","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CE","authors_text":"Junbo Wang, Lei Long, Ruiting Ma, Xin Li, Xuebin Chen, Yiwei Liu, Yuankai Wu","submitted_at":"2025-04-03T09:35:07Z","abstract_excerpt":"Existing financial sentiment analysis methods often fail to capture the multi-faceted nature of risk in bond markets due to their single-level approach and neglect of temporal dynamics. We propose Multi-level Financial Sentiment Analysis (MulFSA) based on pre-trained language models (PLMs) and large language models (LLMs), a novel framework that systematically integrates firm-specific micro-level sentiment, industry-specific meso-level sentiment, and duration-aware smoothing to model the latency and persistence of textual impact. Applying MulFSA to the comprehensive Chinese bond market corpus "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.02429","kind":"arxiv","version":2},"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/2504.02429/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":"2504.02429","created_at":"2026-05-21T01:05:05.242938+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.02429v2","created_at":"2026-05-21T01:05:05.242938+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.02429","created_at":"2026-05-21T01:05:05.242938+00:00"},{"alias_kind":"pith_short_12","alias_value":"J3UFKIZ3KX2V","created_at":"2026-05-21T01:05:05.242938+00:00"},{"alias_kind":"pith_short_16","alias_value":"J3UFKIZ3KX2VN4DE","created_at":"2026-05-21T01:05:05.242938+00:00"},{"alias_kind":"pith_short_8","alias_value":"J3UFKIZ3","created_at":"2026-05-21T01:05:05.242938+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/J3UFKIZ3KX2VN4DEPFRUDA43QG","json":"https://pith.science/pith/J3UFKIZ3KX2VN4DEPFRUDA43QG.json","graph_json":"https://pith.science/api/pith-number/J3UFKIZ3KX2VN4DEPFRUDA43QG/graph.json","events_json":"https://pith.science/api/pith-number/J3UFKIZ3KX2VN4DEPFRUDA43QG/events.json","paper":"https://pith.science/paper/J3UFKIZ3"},"agent_actions":{"view_html":"https://pith.science/pith/J3UFKIZ3KX2VN4DEPFRUDA43QG","download_json":"https://pith.science/pith/J3UFKIZ3KX2VN4DEPFRUDA43QG.json","view_paper":"https://pith.science/paper/J3UFKIZ3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.02429&json=true","fetch_graph":"https://pith.science/api/pith-number/J3UFKIZ3KX2VN4DEPFRUDA43QG/graph.json","fetch_events":"https://pith.science/api/pith-number/J3UFKIZ3KX2VN4DEPFRUDA43QG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/J3UFKIZ3KX2VN4DEPFRUDA43QG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/J3UFKIZ3KX2VN4DEPFRUDA43QG/action/storage_attestation","attest_author":"https://pith.science/pith/J3UFKIZ3KX2VN4DEPFRUDA43QG/action/author_attestation","sign_citation":"https://pith.science/pith/J3UFKIZ3KX2VN4DEPFRUDA43QG/action/citation_signature","submit_replication":"https://pith.science/pith/J3UFKIZ3KX2VN4DEPFRUDA43QG/action/replication_record"}},"created_at":"2026-05-21T01:05:05.242938+00:00","updated_at":"2026-05-21T01:05:05.242938+00:00"}