{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:YU46DDN256MSA67VMMEFYNNLKZ","short_pith_number":"pith:YU46DDN2","canonical_record":{"source":{"id":"1904.10717","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-24T09:41:14Z","cross_cats_sorted":["cs.CL","stat.ML"],"title_canon_sha256":"c3b6a2a6643a0372739902ea3fc93f35434a16002159ac0c43c3b382be94d9f9","abstract_canon_sha256":"262921b9fc975cce49f6d7b9cd9d895a40a312af5bb8574265aa8330ca0a4641"},"schema_version":"1.0"},"canonical_sha256":"c539e18dbaef99207bf563085c35ab56732cf8308eff2e5a2d806ad4675c42a4","source":{"kind":"arxiv","id":"1904.10717","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.10717","created_at":"2026-05-17T23:47:50Z"},{"alias_kind":"arxiv_version","alias_value":"1904.10717v1","created_at":"2026-05-17T23:47:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.10717","created_at":"2026-05-17T23:47:50Z"},{"alias_kind":"pith_short_12","alias_value":"YU46DDN256MS","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"YU46DDN256MSA67V","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"YU46DDN2","created_at":"2026-05-18T12:33:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:YU46DDN256MSA67VMMEFYNNLKZ","target":"record","payload":{"canonical_record":{"source":{"id":"1904.10717","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-24T09:41:14Z","cross_cats_sorted":["cs.CL","stat.ML"],"title_canon_sha256":"c3b6a2a6643a0372739902ea3fc93f35434a16002159ac0c43c3b382be94d9f9","abstract_canon_sha256":"262921b9fc975cce49f6d7b9cd9d895a40a312af5bb8574265aa8330ca0a4641"},"schema_version":"1.0"},"canonical_sha256":"c539e18dbaef99207bf563085c35ab56732cf8308eff2e5a2d806ad4675c42a4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:50.219977Z","signature_b64":"aZd6SGSOBIbOQSoTxwusJZNtkET/ets8kjWKuVDkv0lMQO4KNMrpskScV0VmiSM16MspJwJCczhwFp8iCMfuCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c539e18dbaef99207bf563085c35ab56732cf8308eff2e5a2d806ad4675c42a4","last_reissued_at":"2026-05-17T23:47:50.219093Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:50.219093Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.10717","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":"2026-05-17T23:47:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"32qH10Shf+HbOMHEtc+SZvBw1w/GRSejSNEtaxJPZEooDS86iwBR7xY5zZVXq/EW4UhtIqG+0Swm19nhQr8HDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T07:23:34.972806Z"},"content_sha256":"62dec888b27bd9d121937fef14452425421df003ab9a4787fbd2a05c6ea35562","schema_version":"1.0","event_id":"sha256:62dec888b27bd9d121937fef14452425421df003ab9a4787fbd2a05c6ea35562"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:YU46DDN256MSA67VMMEFYNNLKZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generating Token-Level Explanations for Natural Language Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","stat.ML"],"primary_cat":"cs.LG","authors_text":"Andreas Vlachos, Arpit Mittal, Christos Christodoulopoulos, James Thorne","submitted_at":"2019-04-24T09:41:14Z","abstract_excerpt":"The task of Natural Language Inference (NLI) is widely modeled as supervised sentence pair classification. While there has been a lot of work recently on generating explanations of the predictions of classifiers on a single piece of text, there have been no attempts to generate explanations of classifiers operating on pairs of sentences. In this paper, we show that it is possible to generate token-level explanations for NLI without the need for training data explicitly annotated for this purpose. We use a simple LSTM architecture and evaluate both LIME and Anchor explanations for this task. We"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.10717","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":""},"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":"2026-05-17T23:47:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+KOALCGgFV1p1Q60DRalol+w7LTFTx/Ty0dN+vh1UflPYTOm1cVF68VanGeQgLOf8dXmn5+p63p4wb/Ak69lDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T07:23:34.973162Z"},"content_sha256":"96e6e07241605d870105fab63dc2b9a2b5cc0d14a89af9af35a88428286cdef7","schema_version":"1.0","event_id":"sha256:96e6e07241605d870105fab63dc2b9a2b5cc0d14a89af9af35a88428286cdef7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YU46DDN256MSA67VMMEFYNNLKZ/bundle.json","state_url":"https://pith.science/pith/YU46DDN256MSA67VMMEFYNNLKZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YU46DDN256MSA67VMMEFYNNLKZ/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":"2026-05-30T07:23:34Z","links":{"resolver":"https://pith.science/pith/YU46DDN256MSA67VMMEFYNNLKZ","bundle":"https://pith.science/pith/YU46DDN256MSA67VMMEFYNNLKZ/bundle.json","state":"https://pith.science/pith/YU46DDN256MSA67VMMEFYNNLKZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YU46DDN256MSA67VMMEFYNNLKZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:YU46DDN256MSA67VMMEFYNNLKZ","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":"262921b9fc975cce49f6d7b9cd9d895a40a312af5bb8574265aa8330ca0a4641","cross_cats_sorted":["cs.CL","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-24T09:41:14Z","title_canon_sha256":"c3b6a2a6643a0372739902ea3fc93f35434a16002159ac0c43c3b382be94d9f9"},"schema_version":"1.0","source":{"id":"1904.10717","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.10717","created_at":"2026-05-17T23:47:50Z"},{"alias_kind":"arxiv_version","alias_value":"1904.10717v1","created_at":"2026-05-17T23:47:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.10717","created_at":"2026-05-17T23:47:50Z"},{"alias_kind":"pith_short_12","alias_value":"YU46DDN256MS","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"YU46DDN256MSA67V","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"YU46DDN2","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:96e6e07241605d870105fab63dc2b9a2b5cc0d14a89af9af35a88428286cdef7","target":"graph","created_at":"2026-05-17T23:47:50Z","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"},"paper":{"abstract_excerpt":"The task of Natural Language Inference (NLI) is widely modeled as supervised sentence pair classification. While there has been a lot of work recently on generating explanations of the predictions of classifiers on a single piece of text, there have been no attempts to generate explanations of classifiers operating on pairs of sentences. In this paper, we show that it is possible to generate token-level explanations for NLI without the need for training data explicitly annotated for this purpose. We use a simple LSTM architecture and evaluate both LIME and Anchor explanations for this task. We","authors_text":"Andreas Vlachos, Arpit Mittal, Christos Christodoulopoulos, James Thorne","cross_cats":["cs.CL","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-24T09:41:14Z","title":"Generating Token-Level Explanations for Natural Language Inference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.10717","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":"sha256:62dec888b27bd9d121937fef14452425421df003ab9a4787fbd2a05c6ea35562","target":"record","created_at":"2026-05-17T23:47:50Z","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":"262921b9fc975cce49f6d7b9cd9d895a40a312af5bb8574265aa8330ca0a4641","cross_cats_sorted":["cs.CL","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-04-24T09:41:14Z","title_canon_sha256":"c3b6a2a6643a0372739902ea3fc93f35434a16002159ac0c43c3b382be94d9f9"},"schema_version":"1.0","source":{"id":"1904.10717","kind":"arxiv","version":1}},"canonical_sha256":"c539e18dbaef99207bf563085c35ab56732cf8308eff2e5a2d806ad4675c42a4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c539e18dbaef99207bf563085c35ab56732cf8308eff2e5a2d806ad4675c42a4","first_computed_at":"2026-05-17T23:47:50.219093Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:47:50.219093Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aZd6SGSOBIbOQSoTxwusJZNtkET/ets8kjWKuVDkv0lMQO4KNMrpskScV0VmiSM16MspJwJCczhwFp8iCMfuCg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:47:50.219977Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.10717","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:62dec888b27bd9d121937fef14452425421df003ab9a4787fbd2a05c6ea35562","sha256:96e6e07241605d870105fab63dc2b9a2b5cc0d14a89af9af35a88428286cdef7"],"state_sha256":"5a51e0f87412edba789f3ca5d03bb55328ab823ad245c4a9390022538ec8af47"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Uo5+3EXvZpsexJ13imqlfXduEkp7zoxCp3a1Qd8FUG89qK3K56BPme1dE29pqGaZJbpnl5OcQ8wUztW7iGW2Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T07:23:34.975297Z","bundle_sha256":"98c03ae04e36fed16651f7709d4c05814d15495237574296faea82f082d23ce3"}}