{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:IM33R4CXKDY4LM7ET6MI7YTCDB","short_pith_number":"pith:IM33R4CX","canonical_record":{"source":{"id":"2506.05675","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-06T01:56:05Z","cross_cats_sorted":[],"title_canon_sha256":"72d64e220b8d8102a4a02f780144f28af30b370278437e9febef52427ecad970","abstract_canon_sha256":"4a79c0660b4872d61518eb67df908022aca2c99196522f5d09a9046b7e01cb28"},"schema_version":"1.0"},"canonical_sha256":"4337b8f05750f1c5b3e49f988fe2621866d92698c21aa8910df38db61e4c33f2","source":{"kind":"arxiv","id":"2506.05675","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05675","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05675v2","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05675","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"pith_short_12","alias_value":"IM33R4CXKDY4","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"pith_short_16","alias_value":"IM33R4CXKDY4LM7E","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"pith_short_8","alias_value":"IM33R4CX","created_at":"2026-07-05T11:18:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:IM33R4CXKDY4LM7ET6MI7YTCDB","target":"record","payload":{"canonical_record":{"source":{"id":"2506.05675","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-06T01:56:05Z","cross_cats_sorted":[],"title_canon_sha256":"72d64e220b8d8102a4a02f780144f28af30b370278437e9febef52427ecad970","abstract_canon_sha256":"4a79c0660b4872d61518eb67df908022aca2c99196522f5d09a9046b7e01cb28"},"schema_version":"1.0"},"canonical_sha256":"4337b8f05750f1c5b3e49f988fe2621866d92698c21aa8910df38db61e4c33f2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:18:23.542795Z","signature_b64":"Awqvlc3O6e2Km8dM7axTCuPOxnjdYcL1W1OFz9hev2wgzVdaE0tOvA6KuTucBQKdAKM8VLO9FXJeG+h0X+8UDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4337b8f05750f1c5b3e49f988fe2621866d92698c21aa8910df38db61e4c33f2","last_reissued_at":"2026-07-05T11:18:23.542308Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:18:23.542308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.05675","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:18:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Fbxrh3TUb3Y5yrFaMdLxQ4aiPFdnEhIcAQwLTqnLXC270WSEJEKil0EY7DF9beaT2WX9kO/OhLCGdeKC/yetCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:54:13.465547Z"},"content_sha256":"54a98942fc1e81bf3bce532d2e52cbba93f33e4d86e39d947b837454d1c799bc","schema_version":"1.0","event_id":"sha256:54a98942fc1e81bf3bce532d2e52cbba93f33e4d86e39d947b837454d1c799bc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:IM33R4CXKDY4LM7ET6MI7YTCDB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Zero-Shot Event Causality Identification via Multi-source Evidence Fuzzy Aggregation with Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Qing Cheng, Weiping Ding, Wentao Li, Xingchen Hu, Zefan Zeng, Zhong Liu","submitted_at":"2025-06-06T01:56:05Z","abstract_excerpt":"Event Causality Identification (ECI) aims to detect causal relationships between events in textual contexts. Existing ECI models predominantly rely on supervised methodologies, suffering from dependence on large-scale annotated data. Although Large Language Models (LLMs) enable zero-shot ECI, they are prone to causal hallucination-erroneously establishing spurious causal links. To address these challenges, we propose MEFA, a novel zero-shot framework based on Multi-source Evidence Fuzzy Aggregation. First, we decompose causality reasoning into three main tasks (temporality determination, neces"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05675","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/2506.05675/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:18:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"epjTV8KQIqTmuG19uWW0uobTQGW0fVVuubPnuKF5S48Z43u9jOGpL21ay1v0pFPLVpnW8JPjVJh8pzavnTYVCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T04:54:13.466328Z"},"content_sha256":"a21137c13482f1ad2c1e184a7bab06523a676ae4d1839259c5b325522b6359e6","schema_version":"1.0","event_id":"sha256:a21137c13482f1ad2c1e184a7bab06523a676ae4d1839259c5b325522b6359e6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IM33R4CXKDY4LM7ET6MI7YTCDB/bundle.json","state_url":"https://pith.science/pith/IM33R4CXKDY4LM7ET6MI7YTCDB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IM33R4CXKDY4LM7ET6MI7YTCDB/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-08T04:54:13Z","links":{"resolver":"https://pith.science/pith/IM33R4CXKDY4LM7ET6MI7YTCDB","bundle":"https://pith.science/pith/IM33R4CXKDY4LM7ET6MI7YTCDB/bundle.json","state":"https://pith.science/pith/IM33R4CXKDY4LM7ET6MI7YTCDB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IM33R4CXKDY4LM7ET6MI7YTCDB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:IM33R4CXKDY4LM7ET6MI7YTCDB","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":"4a79c0660b4872d61518eb67df908022aca2c99196522f5d09a9046b7e01cb28","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-06T01:56:05Z","title_canon_sha256":"72d64e220b8d8102a4a02f780144f28af30b370278437e9febef52427ecad970"},"schema_version":"1.0","source":{"id":"2506.05675","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05675","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05675v2","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05675","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"pith_short_12","alias_value":"IM33R4CXKDY4","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"pith_short_16","alias_value":"IM33R4CXKDY4LM7E","created_at":"2026-07-05T11:18:23Z"},{"alias_kind":"pith_short_8","alias_value":"IM33R4CX","created_at":"2026-07-05T11:18:23Z"}],"graph_snapshots":[{"event_id":"sha256:a21137c13482f1ad2c1e184a7bab06523a676ae4d1839259c5b325522b6359e6","target":"graph","created_at":"2026-07-05T11:18:23Z","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/2506.05675/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Event Causality Identification (ECI) aims to detect causal relationships between events in textual contexts. Existing ECI models predominantly rely on supervised methodologies, suffering from dependence on large-scale annotated data. Although Large Language Models (LLMs) enable zero-shot ECI, they are prone to causal hallucination-erroneously establishing spurious causal links. To address these challenges, we propose MEFA, a novel zero-shot framework based on Multi-source Evidence Fuzzy Aggregation. First, we decompose causality reasoning into three main tasks (temporality determination, neces","authors_text":"Qing Cheng, Weiping Ding, Wentao Li, Xingchen Hu, Zefan Zeng, Zhong Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-06T01:56:05Z","title":"Zero-Shot Event Causality Identification via Multi-source Evidence Fuzzy Aggregation with Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05675","kind":"arxiv","version":2},"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":"sha256:54a98942fc1e81bf3bce532d2e52cbba93f33e4d86e39d947b837454d1c799bc","target":"record","created_at":"2026-07-05T11:18:23Z","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":"4a79c0660b4872d61518eb67df908022aca2c99196522f5d09a9046b7e01cb28","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-06T01:56:05Z","title_canon_sha256":"72d64e220b8d8102a4a02f780144f28af30b370278437e9febef52427ecad970"},"schema_version":"1.0","source":{"id":"2506.05675","kind":"arxiv","version":2}},"canonical_sha256":"4337b8f05750f1c5b3e49f988fe2621866d92698c21aa8910df38db61e4c33f2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4337b8f05750f1c5b3e49f988fe2621866d92698c21aa8910df38db61e4c33f2","first_computed_at":"2026-07-05T11:18:23.542308Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:18:23.542308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Awqvlc3O6e2Km8dM7axTCuPOxnjdYcL1W1OFz9hev2wgzVdaE0tOvA6KuTucBQKdAKM8VLO9FXJeG+h0X+8UDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:18:23.542795Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.05675","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:54a98942fc1e81bf3bce532d2e52cbba93f33e4d86e39d947b837454d1c799bc","sha256:a21137c13482f1ad2c1e184a7bab06523a676ae4d1839259c5b325522b6359e6"],"state_sha256":"2ff0deba597b977972e85d511dde4bd9720973e5af7f37ce6cf3ae7292dcfdf9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MHpsrIyWrkGqO/KRDLjDizMZtpkS1ol90dPxj5mq1qBVc0Lg/+LTILPNoexrWcg5/wAPMhbxc/MqYIaskSbpCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T04:54:13.472321Z","bundle_sha256":"71eba93967e4d8488f07e4215cc544269a0376152cdcf49d5205c7075131e4e3"}}