{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:QNBULAX5VLVUSUZOMQDPYMMN7T","short_pith_number":"pith:QNBULAX5","canonical_record":{"source":{"id":"1711.05557","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-11T10:48:59Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"18e0d3d252413d21a0cbaef37ed73d1511166ba78f6906c731dfeb2ceb269b91","abstract_canon_sha256":"aac9fc3030094c447d286a05004ee947991525e98e03b20ac9cd27aa870deb1f"},"schema_version":"1.0"},"canonical_sha256":"83434582fdaaeb49532e6406fc318dfcc79de8d6a42276b3ae4f76ab4dec75fa","source":{"kind":"arxiv","id":"1711.05557","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.05557","created_at":"2026-05-18T00:30:29Z"},{"alias_kind":"arxiv_version","alias_value":"1711.05557v1","created_at":"2026-05-18T00:30:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.05557","created_at":"2026-05-18T00:30:29Z"},{"alias_kind":"pith_short_12","alias_value":"QNBULAX5VLVU","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_16","alias_value":"QNBULAX5VLVUSUZO","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_8","alias_value":"QNBULAX5","created_at":"2026-05-18T12:31:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:QNBULAX5VLVUSUZOMQDPYMMN7T","target":"record","payload":{"canonical_record":{"source":{"id":"1711.05557","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-11T10:48:59Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"18e0d3d252413d21a0cbaef37ed73d1511166ba78f6906c731dfeb2ceb269b91","abstract_canon_sha256":"aac9fc3030094c447d286a05004ee947991525e98e03b20ac9cd27aa870deb1f"},"schema_version":"1.0"},"canonical_sha256":"83434582fdaaeb49532e6406fc318dfcc79de8d6a42276b3ae4f76ab4dec75fa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:30:29.530146Z","signature_b64":"NtkS96npJ1tiybDzjka6kD68JnW8elOKa+Cu+RDBqLO19RqvxnRf1VeToB+4mAKZyUH8mcnjcH9dnVR1rQDcBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83434582fdaaeb49532e6406fc318dfcc79de8d6a42276b3ae4f76ab4dec75fa","last_reissued_at":"2026-05-18T00:30:29.529569Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:30:29.529569Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.05557","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":"2026-05-18T00:30:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c3CQ/6G2u4ZHJs9ZO2lrqDAwqPxSWQqPBqdw09aale9sFYrjfbyAuB1vexq9uqzuYHGKH3hReqayL/25fbPVBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T11:33:39.301660Z"},"content_sha256":"e2b9de6e499d878a69b10af5d76ab868f07dfdae563a221ef645a639be0bbfb5","schema_version":"1.0","event_id":"sha256:e2b9de6e499d878a69b10af5d76ab868f07dfdae563a221ef645a639be0bbfb5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:QNBULAX5VLVUSUZOMQDPYMMN7T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Phrase-based Image Captioning with Hierarchical LSTM Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CV","authors_text":"Chee Seng Chan, Ying Hua Tan","submitted_at":"2017-11-11T10:48:59Z","abstract_excerpt":"Automatic generation of caption to describe the content of an image has been gaining a lot of research interests recently, where most of the existing works treat the image caption as pure sequential data. Natural language, however possess a temporal hierarchy structure, with complex dependencies between each subsequence. In this paper, we propose a phrase-based hierarchical Long Short-Term Memory (phi-LSTM) model to generate image description. In contrast to the conventional solutions that generate caption in a pure sequential manner, our proposed model decodes image caption from phrase to sen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.05557","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":"2026-05-18T00:30:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UTkJKztMole9N/zYxx64f/XjxdvHJzMj7tUrTkddLjccXVx9eXlf7n7LFTIDPcm9jjUrxD5Tlw794EvCs3CxAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T11:33:39.302390Z"},"content_sha256":"bedd6f379f711e676eb97d6cd99729f15990c26bbcfaab2f2e1d2626abd82c5a","schema_version":"1.0","event_id":"sha256:bedd6f379f711e676eb97d6cd99729f15990c26bbcfaab2f2e1d2626abd82c5a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QNBULAX5VLVUSUZOMQDPYMMN7T/bundle.json","state_url":"https://pith.science/pith/QNBULAX5VLVUSUZOMQDPYMMN7T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QNBULAX5VLVUSUZOMQDPYMMN7T/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":"2026-05-23T11:33:39Z","links":{"resolver":"https://pith.science/pith/QNBULAX5VLVUSUZOMQDPYMMN7T","bundle":"https://pith.science/pith/QNBULAX5VLVUSUZOMQDPYMMN7T/bundle.json","state":"https://pith.science/pith/QNBULAX5VLVUSUZOMQDPYMMN7T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QNBULAX5VLVUSUZOMQDPYMMN7T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:QNBULAX5VLVUSUZOMQDPYMMN7T","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":"aac9fc3030094c447d286a05004ee947991525e98e03b20ac9cd27aa870deb1f","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-11T10:48:59Z","title_canon_sha256":"18e0d3d252413d21a0cbaef37ed73d1511166ba78f6906c731dfeb2ceb269b91"},"schema_version":"1.0","source":{"id":"1711.05557","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.05557","created_at":"2026-05-18T00:30:29Z"},{"alias_kind":"arxiv_version","alias_value":"1711.05557v1","created_at":"2026-05-18T00:30:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.05557","created_at":"2026-05-18T00:30:29Z"},{"alias_kind":"pith_short_12","alias_value":"QNBULAX5VLVU","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_16","alias_value":"QNBULAX5VLVUSUZO","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_8","alias_value":"QNBULAX5","created_at":"2026-05-18T12:31:39Z"}],"graph_snapshots":[{"event_id":"sha256:bedd6f379f711e676eb97d6cd99729f15990c26bbcfaab2f2e1d2626abd82c5a","target":"graph","created_at":"2026-05-18T00:30:29Z","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":"Automatic generation of caption to describe the content of an image has been gaining a lot of research interests recently, where most of the existing works treat the image caption as pure sequential data. Natural language, however possess a temporal hierarchy structure, with complex dependencies between each subsequence. In this paper, we propose a phrase-based hierarchical Long Short-Term Memory (phi-LSTM) model to generate image description. In contrast to the conventional solutions that generate caption in a pure sequential manner, our proposed model decodes image caption from phrase to sen","authors_text":"Chee Seng Chan, Ying Hua Tan","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-11T10:48:59Z","title":"Phrase-based Image Captioning with Hierarchical LSTM Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.05557","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:e2b9de6e499d878a69b10af5d76ab868f07dfdae563a221ef645a639be0bbfb5","target":"record","created_at":"2026-05-18T00:30:29Z","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":"aac9fc3030094c447d286a05004ee947991525e98e03b20ac9cd27aa870deb1f","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2017-11-11T10:48:59Z","title_canon_sha256":"18e0d3d252413d21a0cbaef37ed73d1511166ba78f6906c731dfeb2ceb269b91"},"schema_version":"1.0","source":{"id":"1711.05557","kind":"arxiv","version":1}},"canonical_sha256":"83434582fdaaeb49532e6406fc318dfcc79de8d6a42276b3ae4f76ab4dec75fa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"83434582fdaaeb49532e6406fc318dfcc79de8d6a42276b3ae4f76ab4dec75fa","first_computed_at":"2026-05-18T00:30:29.529569Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:30:29.529569Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NtkS96npJ1tiybDzjka6kD68JnW8elOKa+Cu+RDBqLO19RqvxnRf1VeToB+4mAKZyUH8mcnjcH9dnVR1rQDcBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:30:29.530146Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.05557","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e2b9de6e499d878a69b10af5d76ab868f07dfdae563a221ef645a639be0bbfb5","sha256:bedd6f379f711e676eb97d6cd99729f15990c26bbcfaab2f2e1d2626abd82c5a"],"state_sha256":"c1628d0cb033c7418c136dde872587cc21642fc6367a64143c58ca5f0e421e8c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tAV8os8Is9a0G1nC/6J+rAgLjdkqrGNnn34hOh3zSuKXrx77CnFBA7nnucd7gEJmNW2y5UVY8DNDmAiOEx8/Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T11:33:39.309096Z","bundle_sha256":"c7ea962ed394e5e0223ce41866e9aec6d4e7ba803ec77d75b265f0179b00ed9c"}}