{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:4CVALDIMKWF7KFNGGP564DE73Q","short_pith_number":"pith:4CVALDIM","canonical_record":{"source":{"id":"2211.05417","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-10T08:46:53Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dde0757f84dcad8538c49f1d4686455b351fbfbd1d7df66c5195c5ca8faee195","abstract_canon_sha256":"c6f1fee39c6418dd789b6a5c157765310d8802d7993d26a6f67ea362e963cf8d"},"schema_version":"1.0"},"canonical_sha256":"e0aa058d0c558bf515a633fbee0c9fdc17c11a48cedf0593051381a4cfa2f76d","source":{"kind":"arxiv","id":"2211.05417","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.05417","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"arxiv_version","alias_value":"2211.05417v1","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.05417","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"pith_short_12","alias_value":"4CVALDIMKWF7","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"pith_short_16","alias_value":"4CVALDIMKWF7KFNG","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"pith_short_8","alias_value":"4CVALDIM","created_at":"2026-07-05T05:15:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:4CVALDIMKWF7KFNGGP564DE73Q","target":"record","payload":{"canonical_record":{"source":{"id":"2211.05417","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-10T08:46:53Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dde0757f84dcad8538c49f1d4686455b351fbfbd1d7df66c5195c5ca8faee195","abstract_canon_sha256":"c6f1fee39c6418dd789b6a5c157765310d8802d7993d26a6f67ea362e963cf8d"},"schema_version":"1.0"},"canonical_sha256":"e0aa058d0c558bf515a633fbee0c9fdc17c11a48cedf0593051381a4cfa2f76d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:15:04.118989Z","signature_b64":"hNCFC1qwT8qLW/f2IN59VAckAQctcoXeXolVVBAx64jzCTM8CtcphzFiJkfA/pfVVcQ8CNjTG9f4rxRjJ+rNCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e0aa058d0c558bf515a633fbee0c9fdc17c11a48cedf0593051381a4cfa2f76d","last_reissued_at":"2026-07-05T05:15:04.118665Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:15:04.118665Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2211.05417","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":"2026-07-05T05:15:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JrmSqBlKb2wq7uVEZz1Ode9KfZ+rYrGEg1UFTg2TTEZ5oyT1acBZN2GaA3l82+ks4WCbiLaOADZ/5hYduPy3DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T11:37:59.075098Z"},"content_sha256":"205670628236e787e38ebf29e44afebcc5e9b461a16328e7bab35a58c198c597","schema_version":"1.0","event_id":"sha256:205670628236e787e38ebf29e44afebcc5e9b461a16328e7bab35a58c198c597"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:4CVALDIMKWF7KFNGGP564DE73Q","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Can Transformers Reason in Fragments of Natural Language?","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Ian Pratt-Hartmann, Kamen V. Pavlov, Viktor Schlegel","submitted_at":"2022-11-10T08:46:53Z","abstract_excerpt":"State-of-the-art deep-learning-based approaches to Natural Language Processing (NLP) are credited with various capabilities that involve reasoning with natural language texts. In this paper we carry out a large-scale empirical study investigating the detection of formally valid inferences in controlled fragments of natural language for which the satisfiability problem becomes increasingly complex. We find that, while transformer-based language models perform surprisingly well in these scenarios, a deeper analysis re-veals that they appear to overfit to superficial patterns in the data rather t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.05417","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/2211.05417/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":"2026-07-05T05:15:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D8K0Cm5ZhdwFhZ3pZRJV4hsvi/oiicfx67ytM/A4swnNB/FL34mOeU4SFyf04EX532S0SeSS0Jy7RwVVI3RBBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T11:37:59.075607Z"},"content_sha256":"5f775a40479e5effb8b6e73496bf907a51efa9e531f842e7901e6d6b0169a68d","schema_version":"1.0","event_id":"sha256:5f775a40479e5effb8b6e73496bf907a51efa9e531f842e7901e6d6b0169a68d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4CVALDIMKWF7KFNGGP564DE73Q/bundle.json","state_url":"https://pith.science/pith/4CVALDIMKWF7KFNGGP564DE73Q/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4CVALDIMKWF7KFNGGP564DE73Q/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":"2026-08-07T11:37:59Z","links":{"resolver":"https://pith.science/pith/4CVALDIMKWF7KFNGGP564DE73Q","bundle":"https://pith.science/pith/4CVALDIMKWF7KFNGGP564DE73Q/bundle.json","state":"https://pith.science/pith/4CVALDIMKWF7KFNGGP564DE73Q/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4CVALDIMKWF7KFNGGP564DE73Q/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:4CVALDIMKWF7KFNGGP564DE73Q","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":"c6f1fee39c6418dd789b6a5c157765310d8802d7993d26a6f67ea362e963cf8d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-10T08:46:53Z","title_canon_sha256":"dde0757f84dcad8538c49f1d4686455b351fbfbd1d7df66c5195c5ca8faee195"},"schema_version":"1.0","source":{"id":"2211.05417","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.05417","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"arxiv_version","alias_value":"2211.05417v1","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.05417","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"pith_short_12","alias_value":"4CVALDIMKWF7","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"pith_short_16","alias_value":"4CVALDIMKWF7KFNG","created_at":"2026-07-05T05:15:04Z"},{"alias_kind":"pith_short_8","alias_value":"4CVALDIM","created_at":"2026-07-05T05:15:04Z"}],"graph_snapshots":[{"event_id":"sha256:5f775a40479e5effb8b6e73496bf907a51efa9e531f842e7901e6d6b0169a68d","target":"graph","created_at":"2026-07-05T05:15:04Z","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/2211.05417/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"State-of-the-art deep-learning-based approaches to Natural Language Processing (NLP) are credited with various capabilities that involve reasoning with natural language texts. In this paper we carry out a large-scale empirical study investigating the detection of formally valid inferences in controlled fragments of natural language for which the satisfiability problem becomes increasingly complex. We find that, while transformer-based language models perform surprisingly well in these scenarios, a deeper analysis re-veals that they appear to overfit to superficial patterns in the data rather t","authors_text":"Ian Pratt-Hartmann, Kamen V. Pavlov, Viktor Schlegel","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-10T08:46:53Z","title":"Can Transformers Reason in Fragments of Natural Language?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.05417","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":"sha256:205670628236e787e38ebf29e44afebcc5e9b461a16328e7bab35a58c198c597","target":"record","created_at":"2026-07-05T05:15:04Z","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":"c6f1fee39c6418dd789b6a5c157765310d8802d7993d26a6f67ea362e963cf8d","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-11-10T08:46:53Z","title_canon_sha256":"dde0757f84dcad8538c49f1d4686455b351fbfbd1d7df66c5195c5ca8faee195"},"schema_version":"1.0","source":{"id":"2211.05417","kind":"arxiv","version":1}},"canonical_sha256":"e0aa058d0c558bf515a633fbee0c9fdc17c11a48cedf0593051381a4cfa2f76d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0aa058d0c558bf515a633fbee0c9fdc17c11a48cedf0593051381a4cfa2f76d","first_computed_at":"2026-07-05T05:15:04.118665Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:15:04.118665Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hNCFC1qwT8qLW/f2IN59VAckAQctcoXeXolVVBAx64jzCTM8CtcphzFiJkfA/pfVVcQ8CNjTG9f4rxRjJ+rNCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:15:04.118989Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.05417","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:205670628236e787e38ebf29e44afebcc5e9b461a16328e7bab35a58c198c597","sha256:5f775a40479e5effb8b6e73496bf907a51efa9e531f842e7901e6d6b0169a68d"],"state_sha256":"f0461f0417c82498335e41084a8f9ab0ace6c88f58a18ef88da28759e3d18788"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rBpwwGcOXQq1U45NFTAs3pCCKrBEabZPsmNys8eT6tpuyigBSt3YwZ/1BlseSuvT2M7NyqdND5CoseSzuY/sAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T11:37:59.080302Z","bundle_sha256":"5a2f39d4999852ef920c3cf1cc317b9410932186bb732e7c2a0c559915ef7ca1"}}