{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:D5RLPSWW6JOSQMSN3XMWJYE5B2","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":"32e54fb4724f896b50bd26fb76aadcc5e6de6393f7b6f198a169f03f41d689b0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-06T14:42:20Z","title_canon_sha256":"31862e30ab8ed8256e63c1935039031adc44e690559c038855c17544af50bd61"},"schema_version":"1.0","source":{"id":"2506.06133","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.06133","created_at":"2026-07-05T11:17:26Z"},{"alias_kind":"arxiv_version","alias_value":"2506.06133v1","created_at":"2026-07-05T11:17:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.06133","created_at":"2026-07-05T11:17:26Z"},{"alias_kind":"pith_short_12","alias_value":"D5RLPSWW6JOS","created_at":"2026-07-05T11:17:26Z"},{"alias_kind":"pith_short_16","alias_value":"D5RLPSWW6JOSQMSN","created_at":"2026-07-05T11:17:26Z"},{"alias_kind":"pith_short_8","alias_value":"D5RLPSWW","created_at":"2026-07-05T11:17:26Z"}],"graph_snapshots":[{"event_id":"sha256:8858b1a5d7686740fae58cc7421bf4435828183a5ad432c2c8db4c2de1ce951a","target":"graph","created_at":"2026-07-05T11:17:26Z","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/2506.06133/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Natural Language Inference (NLI) is the task of determining whether a sentence pair represents entailment, contradiction, or a neutral relationship. While NLI models perform well on many inference tasks, their ability to handle fine-grained pragmatic inferences, particularly presupposition in conditionals, remains underexplored. In this study, we introduce CONFER, a novel dataset designed to evaluate how NLI models process inference in conditional sentences. We assess the performance of four NLI models, including two pre-trained models, to examine their generalization to conditional reasoning.","authors_text":"Daniel Dumitrescu, Diana Inkpen, Raj Singh, Tara Azin","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-06T14:42:20Z","title":"Let's CONFER: A Dataset for Evaluating Natural Language Inference Models on CONditional InFERence and Presupposition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.06133","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":"sha256:4a6749053d205e3f1089326a90195fecc6657030e6c03c511dcb301b23805734","target":"record","created_at":"2026-07-05T11:17:26Z","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":"32e54fb4724f896b50bd26fb76aadcc5e6de6393f7b6f198a169f03f41d689b0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-06T14:42:20Z","title_canon_sha256":"31862e30ab8ed8256e63c1935039031adc44e690559c038855c17544af50bd61"},"schema_version":"1.0","source":{"id":"2506.06133","kind":"arxiv","version":1}},"canonical_sha256":"1f62b7cad6f25d28324dddd964e09d0e8c8c05e7067314a197d111f04bf7c076","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1f62b7cad6f25d28324dddd964e09d0e8c8c05e7067314a197d111f04bf7c076","first_computed_at":"2026-07-05T11:17:26.264083Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:17:26.264083Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3Pra317bYOcn4aEndQeNWsVnPos1ZM7osLKGnDd5lQ6SQFLWimPNgNaJ/C+d/p1OJ1SX9ljVG4B3COy3dUz5AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:17:26.264613Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.06133","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a6749053d205e3f1089326a90195fecc6657030e6c03c511dcb301b23805734","sha256:8858b1a5d7686740fae58cc7421bf4435828183a5ad432c2c8db4c2de1ce951a"],"state_sha256":"aad936f1f85795fa2e5c3cf2c3f0e0151455b534c4e4903653c1701f3a7f4eb3"}