{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ZP37Y255RMIXESPUGOPI6KI2QX","short_pith_number":"pith:ZP37Y255","canonical_record":{"source":{"id":"2405.10991","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T08:57:00Z","cross_cats_sorted":["cs.AI","stat.ME"],"title_canon_sha256":"65c40c7db40788e9b5ce47ba274e4fe25df2ad3555f0cdc765e147055547da8f","abstract_canon_sha256":"68a8ef98de0923f4d36bdc067df8c8fdd1bbaf8cfa751041d988cb6c0b6f9a03"},"schema_version":"1.0"},"canonical_sha256":"cbf7fc6bbd8b117249f4339e8f291a85f93cf469375f932cce1a24c89bf00586","source":{"kind":"arxiv","id":"2405.10991","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.10991","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"arxiv_version","alias_value":"2405.10991v1","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.10991","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"pith_short_12","alias_value":"ZP37Y255RMIX","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"pith_short_16","alias_value":"ZP37Y255RMIXESPU","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"pith_short_8","alias_value":"ZP37Y255","created_at":"2026-07-05T08:20:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ZP37Y255RMIXESPUGOPI6KI2QX","target":"record","payload":{"canonical_record":{"source":{"id":"2405.10991","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T08:57:00Z","cross_cats_sorted":["cs.AI","stat.ME"],"title_canon_sha256":"65c40c7db40788e9b5ce47ba274e4fe25df2ad3555f0cdc765e147055547da8f","abstract_canon_sha256":"68a8ef98de0923f4d36bdc067df8c8fdd1bbaf8cfa751041d988cb6c0b6f9a03"},"schema_version":"1.0"},"canonical_sha256":"cbf7fc6bbd8b117249f4339e8f291a85f93cf469375f932cce1a24c89bf00586","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:20:31.197337Z","signature_b64":"+Hh/jSs0uN/Cl1r+1yIh/eFBiSAqV+XJoX49FWCd9B314Ukflv9ssLextEnHf16Mg64GOk0HEbx6E3EM5HRfAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cbf7fc6bbd8b117249f4339e8f291a85f93cf469375f932cce1a24c89bf00586","last_reissued_at":"2026-07-05T08:20:31.196816Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:20:31.196816Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.10991","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":"2026-07-05T08:20:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vOHluodMys69PvFbYR5JxjcMRjqvKdddDQLwG/Mt5fzv0IMJRN2LJv4LaWe35lpKGHnejFfx53ycf9VfbMgjAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T01:25:01.736901Z"},"content_sha256":"a6b873bf1c7d7054d4686d43c66a110bf62217e8000d6884c6517812c0f61bf4","schema_version":"1.0","event_id":"sha256:a6b873bf1c7d7054d4686d43c66a110bf62217e8000d6884c6517812c0f61bf4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ZP37Y255RMIXESPUGOPI6KI2QX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Relative Counterfactual Contrastive Learning for Mitigating Pretrained Stance Bias in Stance Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ME"],"primary_cat":"cs.LG","authors_text":"Jiarui Zhang, Shaojuan Wu, Xiaowang Zhang, Zhiyong Feng","submitted_at":"2024-05-16T08:57:00Z","abstract_excerpt":"Stance detection classifies stance relations (namely, Favor, Against, or Neither) between comments and targets. Pretrained language models (PLMs) are widely used to mine the stance relation to improve the performance of stance detection through pretrained knowledge. However, PLMs also embed ``bad'' pretrained knowledge concerning stance into the extracted stance relation semantics, resulting in pretrained stance bias. It is not trivial to measure pretrained stance bias due to its weak quantifiability. In this paper, we propose Relative Counterfactual Contrastive Learning (RCCL), in which pretr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.10991","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/2405.10991/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":"2026-07-05T08:20:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nEY49trucfATMjJ0ZhRwbXbYcSFn5xoo1WwXCK9F2vlnIdD/lQiMmvrWKQzCJeJ8/ha3JwALYzlQE1Rpr9N5BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T01:25:01.737523Z"},"content_sha256":"2d8342af3a652cbdeca559bcf5786f7f0f2ca27af0c4039e3ef545ecb23dabb0","schema_version":"1.0","event_id":"sha256:2d8342af3a652cbdeca559bcf5786f7f0f2ca27af0c4039e3ef545ecb23dabb0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZP37Y255RMIXESPUGOPI6KI2QX/bundle.json","state_url":"https://pith.science/pith/ZP37Y255RMIXESPUGOPI6KI2QX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZP37Y255RMIXESPUGOPI6KI2QX/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":"2026-07-13T01:25:01Z","links":{"resolver":"https://pith.science/pith/ZP37Y255RMIXESPUGOPI6KI2QX","bundle":"https://pith.science/pith/ZP37Y255RMIXESPUGOPI6KI2QX/bundle.json","state":"https://pith.science/pith/ZP37Y255RMIXESPUGOPI6KI2QX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZP37Y255RMIXESPUGOPI6KI2QX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ZP37Y255RMIXESPUGOPI6KI2QX","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":"68a8ef98de0923f4d36bdc067df8c8fdd1bbaf8cfa751041d988cb6c0b6f9a03","cross_cats_sorted":["cs.AI","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T08:57:00Z","title_canon_sha256":"65c40c7db40788e9b5ce47ba274e4fe25df2ad3555f0cdc765e147055547da8f"},"schema_version":"1.0","source":{"id":"2405.10991","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.10991","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"arxiv_version","alias_value":"2405.10991v1","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.10991","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"pith_short_12","alias_value":"ZP37Y255RMIX","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"pith_short_16","alias_value":"ZP37Y255RMIXESPU","created_at":"2026-07-05T08:20:31Z"},{"alias_kind":"pith_short_8","alias_value":"ZP37Y255","created_at":"2026-07-05T08:20:31Z"}],"graph_snapshots":[{"event_id":"sha256:2d8342af3a652cbdeca559bcf5786f7f0f2ca27af0c4039e3ef545ecb23dabb0","target":"graph","created_at":"2026-07-05T08:20:31Z","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/2405.10991/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Stance detection classifies stance relations (namely, Favor, Against, or Neither) between comments and targets. Pretrained language models (PLMs) are widely used to mine the stance relation to improve the performance of stance detection through pretrained knowledge. However, PLMs also embed ``bad'' pretrained knowledge concerning stance into the extracted stance relation semantics, resulting in pretrained stance bias. It is not trivial to measure pretrained stance bias due to its weak quantifiability. In this paper, we propose Relative Counterfactual Contrastive Learning (RCCL), in which pretr","authors_text":"Jiarui Zhang, Shaojuan Wu, Xiaowang Zhang, Zhiyong Feng","cross_cats":["cs.AI","stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T08:57:00Z","title":"Relative Counterfactual Contrastive Learning for Mitigating Pretrained Stance Bias in Stance Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.10991","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:a6b873bf1c7d7054d4686d43c66a110bf62217e8000d6884c6517812c0f61bf4","target":"record","created_at":"2026-07-05T08:20:31Z","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":"68a8ef98de0923f4d36bdc067df8c8fdd1bbaf8cfa751041d988cb6c0b6f9a03","cross_cats_sorted":["cs.AI","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T08:57:00Z","title_canon_sha256":"65c40c7db40788e9b5ce47ba274e4fe25df2ad3555f0cdc765e147055547da8f"},"schema_version":"1.0","source":{"id":"2405.10991","kind":"arxiv","version":1}},"canonical_sha256":"cbf7fc6bbd8b117249f4339e8f291a85f93cf469375f932cce1a24c89bf00586","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cbf7fc6bbd8b117249f4339e8f291a85f93cf469375f932cce1a24c89bf00586","first_computed_at":"2026-07-05T08:20:31.196816Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:20:31.196816Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+Hh/jSs0uN/Cl1r+1yIh/eFBiSAqV+XJoX49FWCd9B314Ukflv9ssLextEnHf16Mg64GOk0HEbx6E3EM5HRfAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:20:31.197337Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.10991","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a6b873bf1c7d7054d4686d43c66a110bf62217e8000d6884c6517812c0f61bf4","sha256:2d8342af3a652cbdeca559bcf5786f7f0f2ca27af0c4039e3ef545ecb23dabb0"],"state_sha256":"133c80da02cb2c2cc286b851ff31684995bb2bc7ed95e0d1c13b515e96fa5bf7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iMnKAXGQ5jzYsOMBZ8QgICEic4xFMoDw03Fu+zrQDD3kpIzqEgeVWL7yoXo35lP3qGktghXbpioJhmSf49G0BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-13T01:25:01.742070Z","bundle_sha256":"eee30b57359d4ee7408d7ebd76821397f37c5bb9a05fa9155f45ff3e0661460f"}}