{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:JRC7HIDPLLKLJMOQ6KWEQYTHOF","short_pith_number":"pith:JRC7HIDP","canonical_record":{"source":{"id":"1812.03283","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-08T08:23:33Z","cross_cats_sorted":[],"title_canon_sha256":"03980c4fc6a77e031936d47e455152dde8dee0fce77746d9521a18f73c58c682","abstract_canon_sha256":"a4ccf79612b0162be53179444016dac3326db29de912f6cfa5e61f73f830ba56"},"schema_version":"1.0"},"canonical_sha256":"4c45f3a06f5ad4b4b1d0f2ac48626771707ec74c23bb641dc35dcfa5ad40f756","source":{"kind":"arxiv","id":"1812.03283","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.03283","created_at":"2026-05-17T23:54:21Z"},{"alias_kind":"arxiv_version","alias_value":"1812.03283v2","created_at":"2026-05-17T23:54:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.03283","created_at":"2026-05-17T23:54:21Z"},{"alias_kind":"pith_short_12","alias_value":"JRC7HIDPLLKL","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"JRC7HIDPLLKLJMOQ","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"JRC7HIDP","created_at":"2026-05-18T12:32:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:JRC7HIDPLLKLJMOQ6KWEQYTHOF","target":"record","payload":{"canonical_record":{"source":{"id":"1812.03283","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-08T08:23:33Z","cross_cats_sorted":[],"title_canon_sha256":"03980c4fc6a77e031936d47e455152dde8dee0fce77746d9521a18f73c58c682","abstract_canon_sha256":"a4ccf79612b0162be53179444016dac3326db29de912f6cfa5e61f73f830ba56"},"schema_version":"1.0"},"canonical_sha256":"4c45f3a06f5ad4b4b1d0f2ac48626771707ec74c23bb641dc35dcfa5ad40f756","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:54:21.860409Z","signature_b64":"A+uWrEXttKncLlXw0fD+2vbByj5SRO2EFCOA0MshpNEa+K1YjSPLAayZI6UlvEiILqUTm2vUHMGACJOEZCzCAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4c45f3a06f5ad4b4b1d0f2ac48626771707ec74c23bb641dc35dcfa5ad40f756","last_reissued_at":"2026-05-17T23:54:21.859849Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:54:21.859849Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.03283","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":"2026-05-17T23:54:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SQhIBVcR8NX9zypGmphdkIExOnT/v9banMnB0OR5HsRkw3iltOBBWn0TmWO1cV3Q2P4eGAoQthAl6e+VGr3MDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T20:02:15.806679Z"},"content_sha256":"0b0c523cd478995a1c741d6dae47742fb33a6031ef05f6d695284cd66c49d225","schema_version":"1.0","event_id":"sha256:0b0c523cd478995a1c741d6dae47742fb33a6031ef05f6d695284cd66c49d225"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:JRC7HIDPLLKLJMOQ6KWEQYTHOF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Attend More Times for Image Captioning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hongtao Lu, Jiajun Du, Yonghua Zhang, Yu Qin","submitted_at":"2018-12-08T08:23:33Z","abstract_excerpt":"Most attention-based image captioning models attend to the image once per word. However, attending once per word is rigid and is easy to miss some information. Attending more times can adjust the attention position, find the missing information back and avoid generating the wrong word. In this paper, we show that attending more times per word can gain improvements in the image captioning task, without increasing the number of parameters. We propose a flexible two-LSTM merge model to make it convenient to encode more attentions than words. Our captioning model uses two LSTMs to encode the word "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.03283","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":""},"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":"2026-05-17T23:54:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3zgrxg5KOQbT108m3GbtxcI8kfTDp/OoGopa39OMVJRsOcf52+P+oa8ymYqmuy99jCsbQcDyXen6AQLqNv8XAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-22T20:02:15.807016Z"},"content_sha256":"ecf0c2f935fe56ce993a6cb014c3d967815ab4c1ff04eb06b9fc1194c0ca2b3c","schema_version":"1.0","event_id":"sha256:ecf0c2f935fe56ce993a6cb014c3d967815ab4c1ff04eb06b9fc1194c0ca2b3c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JRC7HIDPLLKLJMOQ6KWEQYTHOF/bundle.json","state_url":"https://pith.science/pith/JRC7HIDPLLKLJMOQ6KWEQYTHOF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JRC7HIDPLLKLJMOQ6KWEQYTHOF/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":"2026-07-22T20:02:15Z","links":{"resolver":"https://pith.science/pith/JRC7HIDPLLKLJMOQ6KWEQYTHOF","bundle":"https://pith.science/pith/JRC7HIDPLLKLJMOQ6KWEQYTHOF/bundle.json","state":"https://pith.science/pith/JRC7HIDPLLKLJMOQ6KWEQYTHOF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JRC7HIDPLLKLJMOQ6KWEQYTHOF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:JRC7HIDPLLKLJMOQ6KWEQYTHOF","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":"a4ccf79612b0162be53179444016dac3326db29de912f6cfa5e61f73f830ba56","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-08T08:23:33Z","title_canon_sha256":"03980c4fc6a77e031936d47e455152dde8dee0fce77746d9521a18f73c58c682"},"schema_version":"1.0","source":{"id":"1812.03283","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.03283","created_at":"2026-05-17T23:54:21Z"},{"alias_kind":"arxiv_version","alias_value":"1812.03283v2","created_at":"2026-05-17T23:54:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.03283","created_at":"2026-05-17T23:54:21Z"},{"alias_kind":"pith_short_12","alias_value":"JRC7HIDPLLKL","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"JRC7HIDPLLKLJMOQ","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"JRC7HIDP","created_at":"2026-05-18T12:32:31Z"}],"graph_snapshots":[{"event_id":"sha256:ecf0c2f935fe56ce993a6cb014c3d967815ab4c1ff04eb06b9fc1194c0ca2b3c","target":"graph","created_at":"2026-05-17T23:54:21Z","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":"Most attention-based image captioning models attend to the image once per word. However, attending once per word is rigid and is easy to miss some information. Attending more times can adjust the attention position, find the missing information back and avoid generating the wrong word. In this paper, we show that attending more times per word can gain improvements in the image captioning task, without increasing the number of parameters. We propose a flexible two-LSTM merge model to make it convenient to encode more attentions than words. Our captioning model uses two LSTMs to encode the word ","authors_text":"Hongtao Lu, Jiajun Du, Yonghua Zhang, Yu Qin","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-08T08:23:33Z","title":"Attend More Times for Image Captioning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.03283","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":"sha256:0b0c523cd478995a1c741d6dae47742fb33a6031ef05f6d695284cd66c49d225","target":"record","created_at":"2026-05-17T23:54:21Z","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":"a4ccf79612b0162be53179444016dac3326db29de912f6cfa5e61f73f830ba56","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-12-08T08:23:33Z","title_canon_sha256":"03980c4fc6a77e031936d47e455152dde8dee0fce77746d9521a18f73c58c682"},"schema_version":"1.0","source":{"id":"1812.03283","kind":"arxiv","version":2}},"canonical_sha256":"4c45f3a06f5ad4b4b1d0f2ac48626771707ec74c23bb641dc35dcfa5ad40f756","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4c45f3a06f5ad4b4b1d0f2ac48626771707ec74c23bb641dc35dcfa5ad40f756","first_computed_at":"2026-05-17T23:54:21.859849Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:54:21.859849Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A+uWrEXttKncLlXw0fD+2vbByj5SRO2EFCOA0MshpNEa+K1YjSPLAayZI6UlvEiILqUTm2vUHMGACJOEZCzCAQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:54:21.860409Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.03283","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0b0c523cd478995a1c741d6dae47742fb33a6031ef05f6d695284cd66c49d225","sha256:ecf0c2f935fe56ce993a6cb014c3d967815ab4c1ff04eb06b9fc1194c0ca2b3c"],"state_sha256":"9cc081140834281c1b52832cf7b64c2b969faf8239393e5ad2726df68aa702d3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yL0cLQLJWIKbd4lPxLwkt6ldv4wa4c8F1wywQ6hZ1huUSpMX5WKKyEC9sfJelWgTQMdcnon5twBf9ToGOl+iAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-22T20:02:15.809569Z","bundle_sha256":"4f7fd3154f11f86ae0fe8f5e6c1fb7f701c99999790103cdb98ddee379a02ae7"}}