{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:V2Q6BYYLNASM6D3IGS5HXGYQM2","short_pith_number":"pith:V2Q6BYYL","canonical_record":{"source":{"id":"1806.04510","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-08T03:29:30Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0efbcc31ff8c512208e407b7b8282564008a660d51326f9ca90929f051a5a8c1","abstract_canon_sha256":"3b329ec3e0320c593ec6e5de021d24cf3e99bebdb8be6fcfd2cc4e86950a9a91"},"schema_version":"1.0"},"canonical_sha256":"aea1e0e30b6824cf0f6834ba7b9b1066b87f1e59b60f1af6846800177b6e9c0b","source":{"kind":"arxiv","id":"1806.04510","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.04510","created_at":"2026-05-18T00:13:35Z"},{"alias_kind":"arxiv_version","alias_value":"1806.04510v1","created_at":"2026-05-18T00:13:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04510","created_at":"2026-05-18T00:13:35Z"},{"alias_kind":"pith_short_12","alias_value":"V2Q6BYYLNASM","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"V2Q6BYYLNASM6D3I","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"V2Q6BYYL","created_at":"2026-05-18T12:32:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:V2Q6BYYLNASM6D3IGS5HXGYQM2","target":"record","payload":{"canonical_record":{"source":{"id":"1806.04510","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-08T03:29:30Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0efbcc31ff8c512208e407b7b8282564008a660d51326f9ca90929f051a5a8c1","abstract_canon_sha256":"3b329ec3e0320c593ec6e5de021d24cf3e99bebdb8be6fcfd2cc4e86950a9a91"},"schema_version":"1.0"},"canonical_sha256":"aea1e0e30b6824cf0f6834ba7b9b1066b87f1e59b60f1af6846800177b6e9c0b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:35.307018Z","signature_b64":"r6+l8AE/eLT78qHU1u1NJEmWv7mBssvgzHwUrKL+MZsx9NLaqFIJek94k5ShetY3xpLCs8lODhu/1W0/cm2HBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aea1e0e30b6824cf0f6834ba7b9b1066b87f1e59b60f1af6846800177b6e9c0b","last_reissued_at":"2026-05-18T00:13:35.306526Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:35.306526Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.04510","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":"2026-05-18T00:13:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pg0okb9Lztmrx1voVtFKOFlswVntQfrurZby14ZLZSE/qzQGYhv2wA53QB9tn08sxZ06LhUhjZ2MpTj4dUI6Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T13:44:40.241863Z"},"content_sha256":"e74c9f7e51da3b08a3133e7c8d989589f7800fbb13a99458a3353f3207f100de","schema_version":"1.0","event_id":"sha256:e74c9f7e51da3b08a3133e7c8d989589f7800fbb13a99458a3353f3207f100de"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:V2Q6BYYLNASM6D3IGS5HXGYQM2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dank Learning: Generating Memes Using Deep Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Abel L Peirson V, E Meltem Tolunay","submitted_at":"2018-06-08T03:29:30Z","abstract_excerpt":"We introduce a novel meme generation system, which given any image can produce a humorous and relevant caption. Furthermore, the system can be conditioned on not only an image but also a user-defined label relating to the meme template, giving a handle to the user on meme content. The system uses a pretrained Inception-v3 network to return an image embedding which is passed to an attention-based deep-layer LSTM model producing the caption - inspired by the widely recognised Show and Tell Model. We implement a modified beam search to encourage diversity in the captions. We evaluate the quality "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04510","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":"2026-05-18T00:13:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ognCXsKXRGSstUXijz0MT8cHf0FqbbG3kipNHnuwgrQzZ0zrrAY781d7kajEnt68kKhn5mX1aRnLG/rt8RaGBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T13:44:40.242325Z"},"content_sha256":"613f6250c604ab2b689ba4273a1e8f0a0b17ff5f290c1ff7aa39333da8200a1a","schema_version":"1.0","event_id":"sha256:613f6250c604ab2b689ba4273a1e8f0a0b17ff5f290c1ff7aa39333da8200a1a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V2Q6BYYLNASM6D3IGS5HXGYQM2/bundle.json","state_url":"https://pith.science/pith/V2Q6BYYLNASM6D3IGS5HXGYQM2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V2Q6BYYLNASM6D3IGS5HXGYQM2/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":"2026-08-11T13:44:40Z","links":{"resolver":"https://pith.science/pith/V2Q6BYYLNASM6D3IGS5HXGYQM2","bundle":"https://pith.science/pith/V2Q6BYYLNASM6D3IGS5HXGYQM2/bundle.json","state":"https://pith.science/pith/V2Q6BYYLNASM6D3IGS5HXGYQM2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V2Q6BYYLNASM6D3IGS5HXGYQM2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:V2Q6BYYLNASM6D3IGS5HXGYQM2","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":"3b329ec3e0320c593ec6e5de021d24cf3e99bebdb8be6fcfd2cc4e86950a9a91","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-08T03:29:30Z","title_canon_sha256":"0efbcc31ff8c512208e407b7b8282564008a660d51326f9ca90929f051a5a8c1"},"schema_version":"1.0","source":{"id":"1806.04510","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.04510","created_at":"2026-05-18T00:13:35Z"},{"alias_kind":"arxiv_version","alias_value":"1806.04510v1","created_at":"2026-05-18T00:13:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.04510","created_at":"2026-05-18T00:13:35Z"},{"alias_kind":"pith_short_12","alias_value":"V2Q6BYYLNASM","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"V2Q6BYYLNASM6D3I","created_at":"2026-05-18T12:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"V2Q6BYYL","created_at":"2026-05-18T12:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:613f6250c604ab2b689ba4273a1e8f0a0b17ff5f290c1ff7aa39333da8200a1a","target":"graph","created_at":"2026-05-18T00:13:35Z","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":"We introduce a novel meme generation system, which given any image can produce a humorous and relevant caption. Furthermore, the system can be conditioned on not only an image but also a user-defined label relating to the meme template, giving a handle to the user on meme content. The system uses a pretrained Inception-v3 network to return an image embedding which is passed to an attention-based deep-layer LSTM model producing the caption - inspired by the widely recognised Show and Tell Model. We implement a modified beam search to encourage diversity in the captions. We evaluate the quality ","authors_text":"Abel L Peirson V, E Meltem Tolunay","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-08T03:29:30Z","title":"Dank Learning: Generating Memes Using Deep Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.04510","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:e74c9f7e51da3b08a3133e7c8d989589f7800fbb13a99458a3353f3207f100de","target":"record","created_at":"2026-05-18T00:13:35Z","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":"3b329ec3e0320c593ec6e5de021d24cf3e99bebdb8be6fcfd2cc4e86950a9a91","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-06-08T03:29:30Z","title_canon_sha256":"0efbcc31ff8c512208e407b7b8282564008a660d51326f9ca90929f051a5a8c1"},"schema_version":"1.0","source":{"id":"1806.04510","kind":"arxiv","version":1}},"canonical_sha256":"aea1e0e30b6824cf0f6834ba7b9b1066b87f1e59b60f1af6846800177b6e9c0b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aea1e0e30b6824cf0f6834ba7b9b1066b87f1e59b60f1af6846800177b6e9c0b","first_computed_at":"2026-05-18T00:13:35.306526Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:35.306526Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"r6+l8AE/eLT78qHU1u1NJEmWv7mBssvgzHwUrKL+MZsx9NLaqFIJek94k5ShetY3xpLCs8lODhu/1W0/cm2HBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:35.307018Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.04510","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e74c9f7e51da3b08a3133e7c8d989589f7800fbb13a99458a3353f3207f100de","sha256:613f6250c604ab2b689ba4273a1e8f0a0b17ff5f290c1ff7aa39333da8200a1a"],"state_sha256":"ecb8182e305b61f5294b9bc0e6ce2178fbf40849f14d30eb562608b531c0e00c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"egJDAe7HQPvaLCeM9JEwOA/vnNH+D/ReUV54sd0hBBOweiWP3PpWIx4ZZutb8eIDxIM5PewsY32/OofFeha4DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T13:44:40.246145Z","bundle_sha256":"056aaac7397380ed757f4373ba6e2e6cd6bcfdd42b6e7549f454473b47fa784b"}}