{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:DIE44MVXJD23LMGDXSXH4PYIF6","short_pith_number":"pith:DIE44MVX","canonical_record":{"source":{"id":"1612.06890","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-20T21:40:40Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"68ea754ad010f383b5c7f6726413f1b643ca7c0a2e537788eaee73ca9c7668f9","abstract_canon_sha256":"e519d897e7f007c025253c5a3f4dfdeecc70ae6ce3f5e86c7a10739589556166"},"schema_version":"1.0"},"canonical_sha256":"1a09ce32b748f5b5b0c3bcae7e3f082fafd90ebcbea12c0794cbfa973e62e4f3","source":{"kind":"arxiv","id":"1612.06890","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.06890","created_at":"2026-05-18T00:54:15Z"},{"alias_kind":"arxiv_version","alias_value":"1612.06890v1","created_at":"2026-05-18T00:54:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.06890","created_at":"2026-05-18T00:54:15Z"},{"alias_kind":"pith_short_12","alias_value":"DIE44MVXJD23","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"DIE44MVXJD23LMGD","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"DIE44MVX","created_at":"2026-05-18T12:30:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:DIE44MVXJD23LMGDXSXH4PYIF6","target":"record","payload":{"canonical_record":{"source":{"id":"1612.06890","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-20T21:40:40Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"68ea754ad010f383b5c7f6726413f1b643ca7c0a2e537788eaee73ca9c7668f9","abstract_canon_sha256":"e519d897e7f007c025253c5a3f4dfdeecc70ae6ce3f5e86c7a10739589556166"},"schema_version":"1.0"},"canonical_sha256":"1a09ce32b748f5b5b0c3bcae7e3f082fafd90ebcbea12c0794cbfa973e62e4f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:54:15.114171Z","signature_b64":"PSniQUGoxNCxjUlT1mCq8f6hFMZ3wgdIoyvNaxTY+AE1A2T4oPBVrLhQgyfs1VnBZoMg3cGhhaqimFgOZzBCBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1a09ce32b748f5b5b0c3bcae7e3f082fafd90ebcbea12c0794cbfa973e62e4f3","last_reissued_at":"2026-05-18T00:54:15.113488Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:54:15.113488Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1612.06890","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":"2026-05-18T00:54:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5BsxjepTxfM+KflQxJzD5VK2H0fgxJcUumVtPaTp78i6w1C6PYs+szla/2BJWGteP9W54sL+nGjMKG6tlAYFAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T09:33:59.131695Z"},"content_sha256":"46259b0eba4382705a0df716e12116e809cb9c25f140ad234f262af357510ef2","schema_version":"1.0","event_id":"sha256:46259b0eba4382705a0df716e12116e809cb9c25f140ad234f262af357510ef2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:DIE44MVXJD23LMGDXSXH4PYIF6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.CV","authors_text":"Bharath Hariharan, C. Lawrence Zitnick, Justin Johnson, Laurens van der Maaten, Li Fei-Fei, Ross Girshick","submitted_at":"2016-12-20T21:40:40Z","abstract_excerpt":"When building artificial intelligence systems that can reason and answer questions about visual data, we need diagnostic tests to analyze our progress and discover shortcomings. Existing benchmarks for visual question answering can help, but have strong biases that models can exploit to correctly answer questions without reasoning. They also conflate multiple sources of error, making it hard to pinpoint model weaknesses. We present a diagnostic dataset that tests a range of visual reasoning abilities. It contains minimal biases and has detailed annotations describing the kind of reasoning each"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.06890","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":"2026-05-18T00:54:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bPSNCr916NV5ZQ9KfopR7a3LBqK4KlWvy014+UtB8VyrZmMImA0V4H9Yu0NcUMugK6RExfb9dyXWPKk8IgieAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T09:33:59.132042Z"},"content_sha256":"b11b0695fb95794d14a0db04a58a338fa06ae6462ef4267c735b45cdeeab3f02","schema_version":"1.0","event_id":"sha256:b11b0695fb95794d14a0db04a58a338fa06ae6462ef4267c735b45cdeeab3f02"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DIE44MVXJD23LMGDXSXH4PYIF6/bundle.json","state_url":"https://pith.science/pith/DIE44MVXJD23LMGDXSXH4PYIF6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DIE44MVXJD23LMGDXSXH4PYIF6/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":"2026-05-20T09:33:59Z","links":{"resolver":"https://pith.science/pith/DIE44MVXJD23LMGDXSXH4PYIF6","bundle":"https://pith.science/pith/DIE44MVXJD23LMGDXSXH4PYIF6/bundle.json","state":"https://pith.science/pith/DIE44MVXJD23LMGDXSXH4PYIF6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DIE44MVXJD23LMGDXSXH4PYIF6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:DIE44MVXJD23LMGDXSXH4PYIF6","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":"e519d897e7f007c025253c5a3f4dfdeecc70ae6ce3f5e86c7a10739589556166","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-20T21:40:40Z","title_canon_sha256":"68ea754ad010f383b5c7f6726413f1b643ca7c0a2e537788eaee73ca9c7668f9"},"schema_version":"1.0","source":{"id":"1612.06890","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.06890","created_at":"2026-05-18T00:54:15Z"},{"alias_kind":"arxiv_version","alias_value":"1612.06890v1","created_at":"2026-05-18T00:54:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.06890","created_at":"2026-05-18T00:54:15Z"},{"alias_kind":"pith_short_12","alias_value":"DIE44MVXJD23","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_16","alias_value":"DIE44MVXJD23LMGD","created_at":"2026-05-18T12:30:12Z"},{"alias_kind":"pith_short_8","alias_value":"DIE44MVX","created_at":"2026-05-18T12:30:12Z"}],"graph_snapshots":[{"event_id":"sha256:b11b0695fb95794d14a0db04a58a338fa06ae6462ef4267c735b45cdeeab3f02","target":"graph","created_at":"2026-05-18T00:54:15Z","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":"When building artificial intelligence systems that can reason and answer questions about visual data, we need diagnostic tests to analyze our progress and discover shortcomings. Existing benchmarks for visual question answering can help, but have strong biases that models can exploit to correctly answer questions without reasoning. They also conflate multiple sources of error, making it hard to pinpoint model weaknesses. We present a diagnostic dataset that tests a range of visual reasoning abilities. It contains minimal biases and has detailed annotations describing the kind of reasoning each","authors_text":"Bharath Hariharan, C. Lawrence Zitnick, Justin Johnson, Laurens van der Maaten, Li Fei-Fei, Ross Girshick","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-20T21:40:40Z","title":"CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.06890","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":"sha256:46259b0eba4382705a0df716e12116e809cb9c25f140ad234f262af357510ef2","target":"record","created_at":"2026-05-18T00:54:15Z","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":"e519d897e7f007c025253c5a3f4dfdeecc70ae6ce3f5e86c7a10739589556166","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2016-12-20T21:40:40Z","title_canon_sha256":"68ea754ad010f383b5c7f6726413f1b643ca7c0a2e537788eaee73ca9c7668f9"},"schema_version":"1.0","source":{"id":"1612.06890","kind":"arxiv","version":1}},"canonical_sha256":"1a09ce32b748f5b5b0c3bcae7e3f082fafd90ebcbea12c0794cbfa973e62e4f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1a09ce32b748f5b5b0c3bcae7e3f082fafd90ebcbea12c0794cbfa973e62e4f3","first_computed_at":"2026-05-18T00:54:15.113488Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:54:15.113488Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PSniQUGoxNCxjUlT1mCq8f6hFMZ3wgdIoyvNaxTY+AE1A2T4oPBVrLhQgyfs1VnBZoMg3cGhhaqimFgOZzBCBQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:54:15.114171Z","signed_message":"canonical_sha256_bytes"},"source_id":"1612.06890","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:46259b0eba4382705a0df716e12116e809cb9c25f140ad234f262af357510ef2","sha256:b11b0695fb95794d14a0db04a58a338fa06ae6462ef4267c735b45cdeeab3f02"],"state_sha256":"492352ad05a04c41fed1bb2f4a2700130b5913c1f4ba3ba6949b05bda2422d31"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5vXwZPM0R/oksoYy7H9Y/LVcrjB8+2qPev70WpBUlwSoNh6MWM1XzQok+5IASEhaEVvQqKAB1+WB/Q58HggJAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-20T09:33:59.134231Z","bundle_sha256":"7990a95ec17f60c572b14199ff1bcee4457d0a398f4f626407f1f31683b7d9b6"}}