{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:T5H6VIHCOV7QY4JAVTL4WO3JYV","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":"b673f06803294e08cfe3c7ecd52d4d26a62bc25c64e7af8e0c9b0e06523bdb7b","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-09-03T21:12:07Z","title_canon_sha256":"a5f75038f1f8574230e561883620ece1d0f71b18f39160ec226aa349de131f8a"},"schema_version":"1.0","source":{"id":"2509.03725","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.03725","created_at":"2026-07-05T12:04:44Z"},{"alias_kind":"arxiv_version","alias_value":"2509.03725v1","created_at":"2026-07-05T12:04:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.03725","created_at":"2026-07-05T12:04:44Z"},{"alias_kind":"pith_short_12","alias_value":"T5H6VIHCOV7Q","created_at":"2026-07-05T12:04:44Z"},{"alias_kind":"pith_short_16","alias_value":"T5H6VIHCOV7QY4JA","created_at":"2026-07-05T12:04:44Z"},{"alias_kind":"pith_short_8","alias_value":"T5H6VIHC","created_at":"2026-07-05T12:04:44Z"}],"graph_snapshots":[{"event_id":"sha256:1e5c12b65fe062d0f1f4a7ec686af5f0174d04d530aacafefc85e8dd08867076","target":"graph","created_at":"2026-07-05T12:04:44Z","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/2509.03725/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We present the novel approach for stance detection across domains and targets, Metric Learning-Based Few-Shot Learning for Cross-Target and Cross-Domain Stance Detection (MLSD). MLSD utilizes metric learning with triplet loss to capture semantic similarities and differences between stance targets, enhancing domain adaptation. By constructing a discriminative embedding space, MLSD allows a cross-target or cross-domain stance detection model to acquire useful examples from new target domains. We evaluate MLSD in multiple cross-target and cross-domain scenarios across two datasets, showing statis","authors_text":"Parush Gera, Tempestt Neal","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-09-03T21:12:07Z","title":"MLSD: A Novel Few-Shot Learning Approach to Enhance Cross-Target and Cross-Domain Stance Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.03725","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":"sha256:57a305d20c7f8fb20b454910dd7493167d046d66a2aecc862eed8a7573dd543c","target":"record","created_at":"2026-07-05T12:04:44Z","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":"b673f06803294e08cfe3c7ecd52d4d26a62bc25c64e7af8e0c9b0e06523bdb7b","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-09-03T21:12:07Z","title_canon_sha256":"a5f75038f1f8574230e561883620ece1d0f71b18f39160ec226aa349de131f8a"},"schema_version":"1.0","source":{"id":"2509.03725","kind":"arxiv","version":1}},"canonical_sha256":"9f4feaa0e2757f0c7120acd7cb3b69c55717a68ee46c584510592e966a725fde","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9f4feaa0e2757f0c7120acd7cb3b69c55717a68ee46c584510592e966a725fde","first_computed_at":"2026-07-05T12:04:44.773413Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:04:44.773413Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZQo8/y8POrrsNI0AqRsgOGWxG+oQkn18IS7YKyLOLxo79TxCQVv3pRvfXcgnR6ptknN9Mb9mnz9PmWEpng65CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:04:44.773879Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.03725","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:57a305d20c7f8fb20b454910dd7493167d046d66a2aecc862eed8a7573dd543c","sha256:1e5c12b65fe062d0f1f4a7ec686af5f0174d04d530aacafefc85e8dd08867076"],"state_sha256":"6f5007e52470169a9edd95a2ef05b3e74b2755a83c0812c9699ddd150f72a270"}