{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:CBPVGX4WSRMQNUR2Y3BQENJUAL","short_pith_number":"pith:CBPVGX4W","canonical_record":{"source":{"id":"2105.03761","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-08T18:46:33Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"31b92f6fc3937a589b55d63c064b32c849c20230c0f8fe60cf862f2d25f86fb9","abstract_canon_sha256":"ef14922591e9ecaa4c727c5b691bf8e114d74ce6b2c0d457b3ea114376ab8103"},"schema_version":"1.0"},"canonical_sha256":"105f535f96945906d23ac6c302353402d5aae91310673ac64ba8c3bff0e9c331","source":{"kind":"arxiv","id":"2105.03761","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.03761","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"arxiv_version","alias_value":"2105.03761v2","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.03761","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"pith_short_12","alias_value":"CBPVGX4WSRMQ","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"pith_short_16","alias_value":"CBPVGX4WSRMQNUR2","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"pith_short_8","alias_value":"CBPVGX4W","created_at":"2026-07-05T03:06:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:CBPVGX4WSRMQNUR2Y3BQENJUAL","target":"record","payload":{"canonical_record":{"source":{"id":"2105.03761","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-08T18:46:33Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"31b92f6fc3937a589b55d63c064b32c849c20230c0f8fe60cf862f2d25f86fb9","abstract_canon_sha256":"ef14922591e9ecaa4c727c5b691bf8e114d74ce6b2c0d457b3ea114376ab8103"},"schema_version":"1.0"},"canonical_sha256":"105f535f96945906d23ac6c302353402d5aae91310673ac64ba8c3bff0e9c331","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:06:58.448297Z","signature_b64":"v5JyZgltQoXxC1Ii4yrvlwOq2JDr6jSB+RB85/+kICFV/RS8Wgm9lMWXPTelXykWvJClt/FVyTHXS2VKLb7HAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"105f535f96945906d23ac6c302353402d5aae91310673ac64ba8c3bff0e9c331","last_reissued_at":"2026-07-05T03:06:58.447930Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:06:58.447930Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2105.03761","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:06:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xz7R6xkky4iitgtrjKq/Nmq9ovlMAtoOiHr7i8M/VJL34ZOoXDuOuICVcEBmZahUyi03lBV3iNFUnY8UnmLyAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T17:50:25.305806Z"},"content_sha256":"327a7b9935bfb923b5ffea70a39dd19c45fa9337834d20a75a3a4e346fc7a34e","schema_version":"1.0","event_id":"sha256:327a7b9935bfb923b5ffea70a39dd19c45fa9337834d20a75a3a4e346fc7a34e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:CBPVGX4WSRMQNUR2Y3BQENJUAL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.CV","authors_text":"Cornelius Emde, Leonard Salewski, Maxime Kayser, Oana-Maria Camburu, Thomas Lukasiewicz, Virginie Do, Zeynep Akata","submitted_at":"2021-05-08T18:46:33Z","abstract_excerpt":"Recently, there has been an increasing number of efforts to introduce models capable of generating natural language explanations (NLEs) for their predictions on vision-language (VL) tasks. Such models are appealing, because they can provide human-friendly and comprehensive explanations. However, there is a lack of comparison between existing methods, which is due to a lack of re-usable evaluation frameworks and a scarcity of datasets. In this work, we introduce e-ViL and e-SNLI-VE. e-ViL is a benchmark for explainable vision-language tasks that establishes a unified evaluation framework and pr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.03761","kind":"arxiv","version":2},"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/2105.03761/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":"2026-07-05T03:06:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FCaPssTOgqCbpWNSn5vRuswX3uH7GgDgjJwoi5Qzn7Y4dP1SmyEMFqPNBJTMQEfdx1yzbr5ffunxilKlk+ZOBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T17:50:25.306330Z"},"content_sha256":"c79de863651fe10bc61bc06ba5e02fa251ea790a0d7085549cb81dd0e6b05c90","schema_version":"1.0","event_id":"sha256:c79de863651fe10bc61bc06ba5e02fa251ea790a0d7085549cb81dd0e6b05c90"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CBPVGX4WSRMQNUR2Y3BQENJUAL/bundle.json","state_url":"https://pith.science/pith/CBPVGX4WSRMQNUR2Y3BQENJUAL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CBPVGX4WSRMQNUR2Y3BQENJUAL/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":"2026-07-31T17:50:25Z","links":{"resolver":"https://pith.science/pith/CBPVGX4WSRMQNUR2Y3BQENJUAL","bundle":"https://pith.science/pith/CBPVGX4WSRMQNUR2Y3BQENJUAL/bundle.json","state":"https://pith.science/pith/CBPVGX4WSRMQNUR2Y3BQENJUAL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CBPVGX4WSRMQNUR2Y3BQENJUAL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:CBPVGX4WSRMQNUR2Y3BQENJUAL","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":"ef14922591e9ecaa4c727c5b691bf8e114d74ce6b2c0d457b3ea114376ab8103","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-08T18:46:33Z","title_canon_sha256":"31b92f6fc3937a589b55d63c064b32c849c20230c0f8fe60cf862f2d25f86fb9"},"schema_version":"1.0","source":{"id":"2105.03761","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.03761","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"arxiv_version","alias_value":"2105.03761v2","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.03761","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"pith_short_12","alias_value":"CBPVGX4WSRMQ","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"pith_short_16","alias_value":"CBPVGX4WSRMQNUR2","created_at":"2026-07-05T03:06:58Z"},{"alias_kind":"pith_short_8","alias_value":"CBPVGX4W","created_at":"2026-07-05T03:06:58Z"}],"graph_snapshots":[{"event_id":"sha256:c79de863651fe10bc61bc06ba5e02fa251ea790a0d7085549cb81dd0e6b05c90","target":"graph","created_at":"2026-07-05T03:06:58Z","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/2105.03761/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, there has been an increasing number of efforts to introduce models capable of generating natural language explanations (NLEs) for their predictions on vision-language (VL) tasks. Such models are appealing, because they can provide human-friendly and comprehensive explanations. However, there is a lack of comparison between existing methods, which is due to a lack of re-usable evaluation frameworks and a scarcity of datasets. In this work, we introduce e-ViL and e-SNLI-VE. e-ViL is a benchmark for explainable vision-language tasks that establishes a unified evaluation framework and pr","authors_text":"Cornelius Emde, Leonard Salewski, Maxime Kayser, Oana-Maria Camburu, Thomas Lukasiewicz, Virginie Do, Zeynep Akata","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-08T18:46:33Z","title":"e-ViL: A Dataset and Benchmark for Natural Language Explanations in Vision-Language Tasks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.03761","kind":"arxiv","version":2},"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":"sha256:327a7b9935bfb923b5ffea70a39dd19c45fa9337834d20a75a3a4e346fc7a34e","target":"record","created_at":"2026-07-05T03:06:58Z","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":"ef14922591e9ecaa4c727c5b691bf8e114d74ce6b2c0d457b3ea114376ab8103","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-08T18:46:33Z","title_canon_sha256":"31b92f6fc3937a589b55d63c064b32c849c20230c0f8fe60cf862f2d25f86fb9"},"schema_version":"1.0","source":{"id":"2105.03761","kind":"arxiv","version":2}},"canonical_sha256":"105f535f96945906d23ac6c302353402d5aae91310673ac64ba8c3bff0e9c331","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"105f535f96945906d23ac6c302353402d5aae91310673ac64ba8c3bff0e9c331","first_computed_at":"2026-07-05T03:06:58.447930Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:06:58.447930Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"v5JyZgltQoXxC1Ii4yrvlwOq2JDr6jSB+RB85/+kICFV/RS8Wgm9lMWXPTelXykWvJClt/FVyTHXS2VKLb7HAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:06:58.448297Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.03761","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:327a7b9935bfb923b5ffea70a39dd19c45fa9337834d20a75a3a4e346fc7a34e","sha256:c79de863651fe10bc61bc06ba5e02fa251ea790a0d7085549cb81dd0e6b05c90"],"state_sha256":"58cf67b425d71f49e5235719804cb952bc0293b0ade10eda3647a4f09e0fcb09"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"F7tToQDZzm+H+YXDo2H77i4Gnhqmjr/kBBnHbY1HII6J4PKy0HSMvVb2HijKwXTlNwQ/roSYMQBAfg0ikDwJBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T17:50:25.312440Z","bundle_sha256":"ae90f8fb133bf748b8abdd0dfac3c3a1786019d70edb9a264118e2f7cd432dc6"}}