{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:6NO3SYX3MBXUVLQTJKG6WSXGBQ","short_pith_number":"pith:6NO3SYX3","canonical_record":{"source":{"id":"2509.02033","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-02T07:21:36Z","cross_cats_sorted":[],"title_canon_sha256":"94a15b5b1c31888740c02338b33296d24e870f66fa44c74ff5c534056b86fdcb","abstract_canon_sha256":"1132301288bb1482a2eeccabb4eb60b9392801d65d97802cf39f64c2ba7ca76a"},"schema_version":"1.0"},"canonical_sha256":"f35db962fb606f4aae134a8deb4ae60c05a0255e4d4018dc06e1ee45b09218b8","source":{"kind":"arxiv","id":"2509.02033","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.02033","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"arxiv_version","alias_value":"2509.02033v1","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.02033","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"pith_short_12","alias_value":"6NO3SYX3MBXU","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"pith_short_16","alias_value":"6NO3SYX3MBXUVLQT","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"pith_short_8","alias_value":"6NO3SYX3","created_at":"2026-07-05T12:03:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:6NO3SYX3MBXUVLQTJKG6WSXGBQ","target":"record","payload":{"canonical_record":{"source":{"id":"2509.02033","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-02T07:21:36Z","cross_cats_sorted":[],"title_canon_sha256":"94a15b5b1c31888740c02338b33296d24e870f66fa44c74ff5c534056b86fdcb","abstract_canon_sha256":"1132301288bb1482a2eeccabb4eb60b9392801d65d97802cf39f64c2ba7ca76a"},"schema_version":"1.0"},"canonical_sha256":"f35db962fb606f4aae134a8deb4ae60c05a0255e4d4018dc06e1ee45b09218b8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:03:13.339418Z","signature_b64":"qqOJ2TL7lvNIy70AGpc0z5JpkV94ltpbErtEk+FXZ0WV/8rxCYjqZkp5BxSGb5H8Uo6wF3RYkE5WvIhLojbeBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f35db962fb606f4aae134a8deb4ae60c05a0255e4d4018dc06e1ee45b09218b8","last_reissued_at":"2026-07-05T12:03:13.338991Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:03:13.338991Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.02033","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T12:03:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"10TJwUAbHt8KUQNR4OKZh59tfL4VAYTqNe8bapmMlUTTKdcSeaIiGtMtMVw54Ix/oIjwly1vnll/0lbpH0OODQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T03:54:22.812970Z"},"content_sha256":"3c1d9349d8a6366431f1fd7258771daa4baca2a5680dd6470657e3c7a4263c21","schema_version":"1.0","event_id":"sha256:3c1d9349d8a6366431f1fd7258771daa4baca2a5680dd6470657e3c7a4263c21"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:6NO3SYX3MBXUVLQTJKG6WSXGBQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"StructCoh: Structured Contrastive Learning for Context-Aware Text Semantic Matching","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chao Xue, Ziyuan Gao","submitted_at":"2025-09-02T07:21:36Z","abstract_excerpt":"Text semantic matching requires nuanced understanding of both structural relationships and fine-grained semantic distinctions. While pre-trained language models excel at capturing token-level interactions, they often overlook hierarchical structural patterns and struggle with subtle semantic discrimination. In this paper, we proposed StructCoh, a graph-enhanced contrastive learning framework that synergistically combines structural reasoning with representation space optimization. Our approach features two key innovations: (1) A dual-graph encoder constructs semantic graphs via dependency pars"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.02033","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/2509.02033/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":"2026-07-05T12:03:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xbqNA652eH1MnnBzDl8urpNal3Vlmrflq6ZP6/tK/qL+N9eLyxKvGxOdy+gMhteIsBpJxyD4JzNdnv8z3XNICw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T03:54:22.813493Z"},"content_sha256":"71c003c674e7d4143191a611f14f81df824e61e7ea12f160f76dbca779e762ae","schema_version":"1.0","event_id":"sha256:71c003c674e7d4143191a611f14f81df824e61e7ea12f160f76dbca779e762ae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6NO3SYX3MBXUVLQTJKG6WSXGBQ/bundle.json","state_url":"https://pith.science/pith/6NO3SYX3MBXUVLQTJKG6WSXGBQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6NO3SYX3MBXUVLQTJKG6WSXGBQ/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":"2026-08-06T03:54:22Z","links":{"resolver":"https://pith.science/pith/6NO3SYX3MBXUVLQTJKG6WSXGBQ","bundle":"https://pith.science/pith/6NO3SYX3MBXUVLQTJKG6WSXGBQ/bundle.json","state":"https://pith.science/pith/6NO3SYX3MBXUVLQTJKG6WSXGBQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6NO3SYX3MBXUVLQTJKG6WSXGBQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:6NO3SYX3MBXUVLQTJKG6WSXGBQ","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":"1132301288bb1482a2eeccabb4eb60b9392801d65d97802cf39f64c2ba7ca76a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-02T07:21:36Z","title_canon_sha256":"94a15b5b1c31888740c02338b33296d24e870f66fa44c74ff5c534056b86fdcb"},"schema_version":"1.0","source":{"id":"2509.02033","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.02033","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"arxiv_version","alias_value":"2509.02033v1","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.02033","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"pith_short_12","alias_value":"6NO3SYX3MBXU","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"pith_short_16","alias_value":"6NO3SYX3MBXUVLQT","created_at":"2026-07-05T12:03:13Z"},{"alias_kind":"pith_short_8","alias_value":"6NO3SYX3","created_at":"2026-07-05T12:03:13Z"}],"graph_snapshots":[{"event_id":"sha256:71c003c674e7d4143191a611f14f81df824e61e7ea12f160f76dbca779e762ae","target":"graph","created_at":"2026-07-05T12:03:13Z","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/2509.02033/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text semantic matching requires nuanced understanding of both structural relationships and fine-grained semantic distinctions. While pre-trained language models excel at capturing token-level interactions, they often overlook hierarchical structural patterns and struggle with subtle semantic discrimination. In this paper, we proposed StructCoh, a graph-enhanced contrastive learning framework that synergistically combines structural reasoning with representation space optimization. Our approach features two key innovations: (1) A dual-graph encoder constructs semantic graphs via dependency pars","authors_text":"Chao Xue, Ziyuan Gao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-02T07:21:36Z","title":"StructCoh: Structured Contrastive Learning for Context-Aware Text Semantic Matching"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.02033","kind":"arxiv","version":1},"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":"sha256:3c1d9349d8a6366431f1fd7258771daa4baca2a5680dd6470657e3c7a4263c21","target":"record","created_at":"2026-07-05T12:03:13Z","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":"1132301288bb1482a2eeccabb4eb60b9392801d65d97802cf39f64c2ba7ca76a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-02T07:21:36Z","title_canon_sha256":"94a15b5b1c31888740c02338b33296d24e870f66fa44c74ff5c534056b86fdcb"},"schema_version":"1.0","source":{"id":"2509.02033","kind":"arxiv","version":1}},"canonical_sha256":"f35db962fb606f4aae134a8deb4ae60c05a0255e4d4018dc06e1ee45b09218b8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f35db962fb606f4aae134a8deb4ae60c05a0255e4d4018dc06e1ee45b09218b8","first_computed_at":"2026-07-05T12:03:13.338991Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:03:13.338991Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qqOJ2TL7lvNIy70AGpc0z5JpkV94ltpbErtEk+FXZ0WV/8rxCYjqZkp5BxSGb5H8Uo6wF3RYkE5WvIhLojbeBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:03:13.339418Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.02033","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3c1d9349d8a6366431f1fd7258771daa4baca2a5680dd6470657e3c7a4263c21","sha256:71c003c674e7d4143191a611f14f81df824e61e7ea12f160f76dbca779e762ae"],"state_sha256":"a7439eafa53d65fd6a088c7e6825a9babfb0532e84561604d0fda4ab845255e1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PB/l9sw/52s+4tn95xmOB/8Zvnpuk98MsQ+X644BWYwX14/5wiMjCB1+V1MKWRJ2Vuh0tbvg0Jl6o54LATxsAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T03:54:22.818461Z","bundle_sha256":"45c0342cea0126b22933cdb5f19c5a5f51730d73cef6c565e60cc487b5ef711f"}}