{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:RXSHRY7H2JIONONGJS6Z2J4HYO","short_pith_number":"pith:RXSHRY7H","schema_version":"1.0","canonical_sha256":"8de478e3e7d250e6b9a64cbd9d2787c3af109fc81f633bd478019e8ab072f5d2","source":{"kind":"arxiv","id":"2502.07717","version":1},"attestation_state":"computed","paper":{"title":"Making Language Models Robust Against Negation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Eduardo Blanco, MohammadHossein Rezaei","submitted_at":"2025-02-11T17:18:47Z","abstract_excerpt":"Negation has been a long-standing challenge for language models. Previous studies have shown that they struggle with negation in many natural language understanding tasks. In this work, we propose a self-supervised method to make language models more robust against negation. We introduce a novel task, Next Sentence Polarity Prediction (NSPP), and a variation of the Next Sentence Prediction (NSP) task. We show that BERT and RoBERTa further pre-trained on our tasks outperform the off-the-shelf versions on nine negation-related benchmarks. Most notably, our pre-training tasks yield between 1.8% a"},"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":"2502.07717","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-11T17:18:47Z","cross_cats_sorted":[],"title_canon_sha256":"3eeb24bd441a4ee45e51045ca7238834a64f0d97afd1b9566459c383a082029c","abstract_canon_sha256":"3c0cace90a969fcd8ba930948103bc020dfd32f0a93a472f31eb130d6c155f49"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:12:52.957982Z","signature_b64":"WujK9fljze7/LJXaTXOfMRmzTKYihIJDhxWQ0uEkExDdp3WaGxR3g0YqmWfHfqYoVZFdSWPz2uYx2WCKSoUEAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8de478e3e7d250e6b9a64cbd9d2787c3af109fc81f633bd478019e8ab072f5d2","last_reissued_at":"2026-07-05T10:12:52.957588Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:12:52.957588Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Making Language Models Robust Against Negation","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Eduardo Blanco, MohammadHossein Rezaei","submitted_at":"2025-02-11T17:18:47Z","abstract_excerpt":"Negation has been a long-standing challenge for language models. Previous studies have shown that they struggle with negation in many natural language understanding tasks. In this work, we propose a self-supervised method to make language models more robust against negation. We introduce a novel task, Next Sentence Polarity Prediction (NSPP), and a variation of the Next Sentence Prediction (NSP) task. We show that BERT and RoBERTa further pre-trained on our tasks outperform the off-the-shelf versions on nine negation-related benchmarks. Most notably, our pre-training tasks yield between 1.8% a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.07717","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/2502.07717/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":"2502.07717","created_at":"2026-07-05T10:12:52.957643+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.07717v1","created_at":"2026-07-05T10:12:52.957643+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.07717","created_at":"2026-07-05T10:12:52.957643+00:00"},{"alias_kind":"pith_short_12","alias_value":"RXSHRY7H2JIO","created_at":"2026-07-05T10:12:52.957643+00:00"},{"alias_kind":"pith_short_16","alias_value":"RXSHRY7H2JIONONG","created_at":"2026-07-05T10:12:52.957643+00:00"},{"alias_kind":"pith_short_8","alias_value":"RXSHRY7H","created_at":"2026-07-05T10:12:52.957643+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/RXSHRY7H2JIONONGJS6Z2J4HYO","json":"https://pith.science/pith/RXSHRY7H2JIONONGJS6Z2J4HYO.json","graph_json":"https://pith.science/api/pith-number/RXSHRY7H2JIONONGJS6Z2J4HYO/graph.json","events_json":"https://pith.science/api/pith-number/RXSHRY7H2JIONONGJS6Z2J4HYO/events.json","paper":"https://pith.science/paper/RXSHRY7H"},"agent_actions":{"view_html":"https://pith.science/pith/RXSHRY7H2JIONONGJS6Z2J4HYO","download_json":"https://pith.science/pith/RXSHRY7H2JIONONGJS6Z2J4HYO.json","view_paper":"https://pith.science/paper/RXSHRY7H","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.07717&json=true","fetch_graph":"https://pith.science/api/pith-number/RXSHRY7H2JIONONGJS6Z2J4HYO/graph.json","fetch_events":"https://pith.science/api/pith-number/RXSHRY7H2JIONONGJS6Z2J4HYO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RXSHRY7H2JIONONGJS6Z2J4HYO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RXSHRY7H2JIONONGJS6Z2J4HYO/action/storage_attestation","attest_author":"https://pith.science/pith/RXSHRY7H2JIONONGJS6Z2J4HYO/action/author_attestation","sign_citation":"https://pith.science/pith/RXSHRY7H2JIONONGJS6Z2J4HYO/action/citation_signature","submit_replication":"https://pith.science/pith/RXSHRY7H2JIONONGJS6Z2J4HYO/action/replication_record"}},"created_at":"2026-07-05T10:12:52.957643+00:00","updated_at":"2026-07-05T10:12:52.957643+00:00"}