{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:S56KTTS7CUG4WP25MFKXWBSUKJ","short_pith_number":"pith:S56KTTS7","canonical_record":{"source":{"id":"2010.05001","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-10T13:47:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"387e79af0cd1486a076c187d18bb3c5fcfe77c43024de357745ab293d97cc8b9","abstract_canon_sha256":"de06b6bd07df1edffac3ee877325bbb3c979ab850577d3e607244055acbaad5a"},"schema_version":"1.0"},"canonical_sha256":"977ca9ce5f150dcb3f5d61557b06545272f0cfc671df399f1c0d109f1b2c3223","source":{"kind":"arxiv","id":"2010.05001","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.05001","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"arxiv_version","alias_value":"2010.05001v1","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.05001","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"pith_short_12","alias_value":"S56KTTS7CUG4","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"pith_short_16","alias_value":"S56KTTS7CUG4WP25","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"pith_short_8","alias_value":"S56KTTS7","created_at":"2026-07-05T01:42:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:S56KTTS7CUG4WP25MFKXWBSUKJ","target":"record","payload":{"canonical_record":{"source":{"id":"2010.05001","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-10T13:47:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"387e79af0cd1486a076c187d18bb3c5fcfe77c43024de357745ab293d97cc8b9","abstract_canon_sha256":"de06b6bd07df1edffac3ee877325bbb3c979ab850577d3e607244055acbaad5a"},"schema_version":"1.0"},"canonical_sha256":"977ca9ce5f150dcb3f5d61557b06545272f0cfc671df399f1c0d109f1b2c3223","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:42:01.807413Z","signature_b64":"Z75AhAM/qwe5wnXHQmAQxIffmmhIQipfx9vNbiHGxXql3gyf+Ys/RCTMLZxjw9c9kGcTN+lSOtoQGYJLwRVMAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"977ca9ce5f150dcb3f5d61557b06545272f0cfc671df399f1c0d109f1b2c3223","last_reissued_at":"2026-07-05T01:42:01.806932Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:42:01.806932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.05001","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":"2026-07-05T01:42:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MGvCLd/g8ylYRF2swBWFZbiEzST3hQXmJFPScoJYFQzZACRqSkMLG0gup/bBIk0NNkTt0OF7bqaEa3y0fpZKCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T15:39:22.124515Z"},"content_sha256":"12f7a4aca2f735caa99b0ffff16f7d504d5a55223ffd7d1573194239d4199751","schema_version":"1.0","event_id":"sha256:12f7a4aca2f735caa99b0ffff16f7d504d5a55223ffd7d1573194239d4199751"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:S56KTTS7CUG4WP25MFKXWBSUKJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Beyond Language: Learning Commonsense from Images for Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Jiafeng Guo, Liang Pang, Wanqing Cui, Xueqi Cheng, Yanyan Lan","submitted_at":"2020-10-10T13:47:13Z","abstract_excerpt":"This paper proposes a novel approach to learn commonsense from images, instead of limited raw texts or costly constructed knowledge bases, for the commonsense reasoning problem in NLP. Our motivation comes from the fact that an image is worth a thousand words, where richer scene information could be leveraged to help distill the commonsense knowledge, which is often hidden in languages. Our approach, namely Loire, consists of two stages. In the first stage, a bi-modal sequence-to-sequence approach is utilized to conduct the scene layout generation task, based on a text representation model ViB"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.05001","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/2010.05001/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":"2026-07-05T01:42:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qSGOV61UVFL85fnLU6+f+lxsZDkbZ4NodoiJ6Q+6DE0QFMrzb4ljeAqpor8qGF0B3xV7bvqfyZ/jVszeT+1ICg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T15:39:22.124958Z"},"content_sha256":"2c3bcf59062f62b35eeac4e68306c1eca4fb7cf37d63ec37dc98e8de714b6224","schema_version":"1.0","event_id":"sha256:2c3bcf59062f62b35eeac4e68306c1eca4fb7cf37d63ec37dc98e8de714b6224"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S56KTTS7CUG4WP25MFKXWBSUKJ/bundle.json","state_url":"https://pith.science/pith/S56KTTS7CUG4WP25MFKXWBSUKJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S56KTTS7CUG4WP25MFKXWBSUKJ/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":"2026-07-31T15:39:22Z","links":{"resolver":"https://pith.science/pith/S56KTTS7CUG4WP25MFKXWBSUKJ","bundle":"https://pith.science/pith/S56KTTS7CUG4WP25MFKXWBSUKJ/bundle.json","state":"https://pith.science/pith/S56KTTS7CUG4WP25MFKXWBSUKJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S56KTTS7CUG4WP25MFKXWBSUKJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:S56KTTS7CUG4WP25MFKXWBSUKJ","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":"de06b6bd07df1edffac3ee877325bbb3c979ab850577d3e607244055acbaad5a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-10T13:47:13Z","title_canon_sha256":"387e79af0cd1486a076c187d18bb3c5fcfe77c43024de357745ab293d97cc8b9"},"schema_version":"1.0","source":{"id":"2010.05001","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.05001","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"arxiv_version","alias_value":"2010.05001v1","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.05001","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"pith_short_12","alias_value":"S56KTTS7CUG4","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"pith_short_16","alias_value":"S56KTTS7CUG4WP25","created_at":"2026-07-05T01:42:01Z"},{"alias_kind":"pith_short_8","alias_value":"S56KTTS7","created_at":"2026-07-05T01:42:01Z"}],"graph_snapshots":[{"event_id":"sha256:2c3bcf59062f62b35eeac4e68306c1eca4fb7cf37d63ec37dc98e8de714b6224","target":"graph","created_at":"2026-07-05T01:42:01Z","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/2010.05001/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper proposes a novel approach to learn commonsense from images, instead of limited raw texts or costly constructed knowledge bases, for the commonsense reasoning problem in NLP. Our motivation comes from the fact that an image is worth a thousand words, where richer scene information could be leveraged to help distill the commonsense knowledge, which is often hidden in languages. Our approach, namely Loire, consists of two stages. In the first stage, a bi-modal sequence-to-sequence approach is utilized to conduct the scene layout generation task, based on a text representation model ViB","authors_text":"Jiafeng Guo, Liang Pang, Wanqing Cui, Xueqi Cheng, Yanyan Lan","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-10T13:47:13Z","title":"Beyond Language: Learning Commonsense from Images for Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.05001","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":"sha256:12f7a4aca2f735caa99b0ffff16f7d504d5a55223ffd7d1573194239d4199751","target":"record","created_at":"2026-07-05T01:42:01Z","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":"de06b6bd07df1edffac3ee877325bbb3c979ab850577d3e607244055acbaad5a","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-10-10T13:47:13Z","title_canon_sha256":"387e79af0cd1486a076c187d18bb3c5fcfe77c43024de357745ab293d97cc8b9"},"schema_version":"1.0","source":{"id":"2010.05001","kind":"arxiv","version":1}},"canonical_sha256":"977ca9ce5f150dcb3f5d61557b06545272f0cfc671df399f1c0d109f1b2c3223","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"977ca9ce5f150dcb3f5d61557b06545272f0cfc671df399f1c0d109f1b2c3223","first_computed_at":"2026-07-05T01:42:01.806932Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:42:01.806932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Z75AhAM/qwe5wnXHQmAQxIffmmhIQipfx9vNbiHGxXql3gyf+Ys/RCTMLZxjw9c9kGcTN+lSOtoQGYJLwRVMAw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:42:01.807413Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.05001","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:12f7a4aca2f735caa99b0ffff16f7d504d5a55223ffd7d1573194239d4199751","sha256:2c3bcf59062f62b35eeac4e68306c1eca4fb7cf37d63ec37dc98e8de714b6224"],"state_sha256":"75b3b29503a96c452f1744632acda19a1c87c0f09ca983ee8060f53bd375533f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ErUFXN0DwRvPw7NPACMIYmLSfunWdwKPlsuTjJx0jN1eiB7LvVvhQ/3d3xdHbd/HKOOi/IAUyA3FPYPShZB5DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T15:39:22.128622Z","bundle_sha256":"4269844ea716e5f8d0425d6431b01c909eecd69fd56137ad90329c1bf0da1101"}}