{"as_of":"2026-08-13T09:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:91337836ea171efa559ba2a872546349883b3773f82b0c58665199c12a6c4e21","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-24T21:42:20.194268Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T23:09:14.760420Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-11T16:21:06.398788Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1907.06370","snapshot_observed_at":"2026-08-11T23:09:14.760420Z","title":"Multimodal deep networks for text and image-based document classification,","venue":null,"work_id":null,"year":1907},"citing_paper":{"arxiv_id":"2412.02805","last_updated":"2024-12-03T20:17:39Z","snapshot_observed_at":"2026-08-12T07:39:40.586290Z","submitted_at":"2024-12-03T20:17:39Z","title":"STORM: Strategic Orchestration of Modalities for Rare Event Classification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T23:09:14.760420Z"},"links":{"cited_paper":"/paper/1907.06370","citing_paper":"/paper/2412.02805"},"observation_digest":"sha256:caff18ce721e8f91ee65b7d1905309e42ad6727ae5782dc27295d0b334a8c646","observation_id":"2f14f9d6-b3d2-4ed3-bae5-e44846f08e23","resolution":{"observed_at":"2026-08-11T23:09:14.760420Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"cited_work":{"arxiv_id":"1907.06370","doi":null,"metadata_source":"pith","pith_arxiv_id":"1907.06370","snapshot_observed_at":"2026-08-11T16:21:06.398788Z","title":"Multimodal deep networks for text and image-based document classification","venue":"cs.CV","work_id":"1510c8db-0c6e-4cb1-9135-dbfec1ef3646","year":2019},"citing_paper":{"arxiv_id":"2412.10155","last_updated":"2024-12-13T14:12:55Z","snapshot_observed_at":"2026-08-12T07:39:12.154632Z","submitted_at":"2024-12-13T14:12:55Z","title":"WordVIS: A Color Worth A Thousand Words","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T16:21:06.070650Z"},"links":{"cited_paper":"/paper/1907.06370","citing_paper":"/paper/2412.10155"},"observation_digest":"sha256:081ea220977d162a6f693c9d3eaf9b7ec6d78ae8df23237c5444085b8eb248ec","observation_id":"887f58c5-5661-4ee7-aced-79028738d899","resolution":{"observed_at":"2026-08-11T16:21:06.403367Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1907.06370/citation-record","integrity":"/paper/1907.06370/integrity","json":"/paper/1907.06370/citation-record.json","paper":"/paper/1907.06370"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval","venue":null,"work_id":"e154528f-0f15-4075-9bc4-f7bfb4e3ccd7","year":2015},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:b7f2d713d425562204ff34171dd0ac2286109fa8ff6d06d605e433e5696a9e33","observation_id":"ce50bfb0-9156-4153-b6b0-653f9aa3d8d2","resolution":{"observed_at":"2026-05-24T21:45:01.084302Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Document Analysis System","venue":null,"work_id":"cf176047-9a00-488c-8883-aaa79e36ecaf","year":1982},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:b5c3ae9b7e3d66863d03031d6525604e48896e53c6dfdd7962b4955142cdfb1c","observation_id":"4df5349f-14b8-4232-b699-f67dfa415f60","resolution":{"observed_at":"2026-05-24T21:45:01.080295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tesseract: An Open-Source Optical Character Recognition Engine","venue":null,"work_id":"327bdc90-cab1-4f80-8765-75b22ce5212d","year":2007},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:6c8fda04b0d6fc0021d1e5a072e4b97b96cccc8d7d669e1ca6246b51b08e2530","observation_id":"95fb7b23-ddc4-4279-82f6-009d78d255ad","resolution":{"observed_at":"2026-05-24T21:45:01.072918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Classification of binary document images into textual or nontextual data blocks using neural network models","venue":null,"work_id":"6fedf677-ebd8-4c02-8e71-c9904f8b45a3","year":1995},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:e2503a2ba328adee67da22aae5f6059b982fa0fd2e8fe8958f0d4272f306155f","observation_id":"1f35c377-b2b1-4045-9a44-b2ae6b9f4f38","resolution":{"observed_at":"2026-05-24T21:45:01.109545Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Segmentation and classification for mixed text/image documents using neural network","venue":null,"work_id":"85144587-8415-4667-850f-685f4d784489","year":1993},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:dacb3af9bafb31d9d662fd5dd1087d12c209a40eb004af5bc6da3c2db837d87c","observation_id":"071b8a6b-827f-40fc-b7b3-7012649e6db5","resolution":{"observed_at":"2026-05-24T21:45:01.069904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Gradient-based learning applied to document recognition","venue":null,"work_id":"5a6af68a-143e-4d80-ab69-d4baaf062d42","year":1998},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:75c9bb260cc41f1e6646c8df435378c5db4a151e7c316ffc2024db6e4913621f","observation_id":"18e026dc-46d8-4035-b931-8e089584f625","resolution":{"observed_at":"2026-05-24T21:45:01.065920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A survey of document image classification","venue":null,"work_id":"932827d5-26b6-4342-bc6e-7af016a09cc2","year":2007},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:7af1c37795840d5e06a5654880c79b24a66a214eca69faeddb1609052a65c020","observation_id":"1700e1fa-6b59-45b5-a9fe-eec5e149613a","resolution":{"observed_at":"2026-05-24T21:45:01.120039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Structural similarity for document image classification and retrieval","venue":null,"work_id":"694db2e2-571f-4bd1-a914-753f965bcbc1","year":2014},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:9d623e776574b0a2b767b8695452d87e0045d9aa05132e75aa1dd813bbf7eadd","observation_id":"3dcfec9f-4678-4b9e-975f-95e688b2c9fa","resolution":{"observed_at":"2026-05-24T21:45:01.124056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Analysis of CNNs for Document Image Classification","venue":null,"work_id":"7ea2a56f-45d5-455f-a0e2-87ac71c2edeb","year":2017},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:1cfbed8444e8f7bfae0ec3128e0601ab1a9c5237f46830f95c46108e1c908f47","observation_id":"cb7a34ee-e8f8-4f9f-8e21-829fb6f892bb","resolution":{"observed_at":"2026-05-24T21:45:01.058474Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cutting the Error by Half: Investigation of V ery Deep CNN and Advanced Training Strategies for Document Image Classification","venue":null,"work_id":"141b572e-6f06-499f-b7dc-d1e8bdf51526","year":2017},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:d4852f3c239bb5ed5c72b0245800127b0f6858f8041568d5e8751f8879de4dd2","observation_id":"1e9de73b-ce5b-48ce-89d5-d9eea933ffa9","resolution":{"observed_at":"2026-05-24T21:45:01.054840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Document Image Classification with Intra- Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks","venue":null,"work_id":"91f94f3f-09dd-49b8-9497-f10d704bd63f","year":2018},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:79d68cee775c27800adf9fbdaa56102e4256479759a9bdae4e1452c8eb919a05","observation_id":"74084279-2db5-49c7-a918-62aec3b3d25f","resolution":{"observed_at":"2026-05-24T21:45:01.136436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Identity Documents Classification as an Image Classification Problem","venue":null,"work_id":"4ee49e73-dc88-4285-8cb9-e8928d6196ed","year":2017},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:e1618dc020c260e437dfba520b4c176f074929495759b09e2138a686a09da0f6","observation_id":"58d90e45-296e-4a95-bb4a-558bdfcf8baa","resolution":{"observed_at":"2026-05-24T21:45:01.140226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"dhSegment : A generic deep-learning approach for document segmentation","venue":null,"work_id":"28da6db8-94a4-43cc-9345-4d57ef2de10a","year":2018},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:812cc1cc7295fc67d060a96cdb1db0fc33d2d020e54ed713ac4cf51720243aff","observation_id":"1050fe84-13d6-4363-aa37-a598014c43e7","resolution":{"observed_at":"2026-05-24T21:45:01.043048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Automatic Document Classification","venue":null,"work_id":"3b3365b9-00c4-451b-a7c6-f5e29238369b","year":1963},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:7f2aed383ed4323ba41a9660df9e4818919e03f7ee70d120f1d5c4ba6223caba","observation_id":"8e0c21a6-2daf-4ba0-a639-3055c09fb33c","resolution":{"observed_at":"2026-05-24T21:45:01.019635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"One-Class SVMs for Document Classification","venue":null,"work_id":"4e952a22-d1ee-45a6-89fe-bc0de7bcbe1f","year":2001},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:22967ba098390c8c9a7af9f60f8d4665c0c57b54597f58346637ee0b0fada077","observation_id":"af32755f-3e60-4fe7-9cdf-1db20f2fdb52","resolution":{"observed_at":"2026-05-24T21:45:01.091662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Statistical topic models for multi-label document classification","venue":null,"work_id":"5aeae7d1-39f3-4f41-aca7-d2a68433cd66","year":2012},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:1d93ef573a44900d8fdde1065359598b61415bddbb82907cb492949305672976","observation_id":"fab47132-2b3f-4c6f-b483-53c1311ef1b6","resolution":{"observed_at":"2026-05-24T21:45:01.095450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Efficient Estimation of W ord Representations in V ector Space","venue":null,"work_id":"263925e7-1d75-4255-bdef-23c11cf16ffd","year":2013},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:48f4a91039b96a2961d390a41e047a0b77a461c911cc5f5ef249adc2dd2f8c76","observation_id":"5e34062f-1b64-4014-afec-c7568125d969","resolution":{"observed_at":"2026-05-24T21:45:01.099363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep Contextualized W ord Representations","venue":null,"work_id":"d94c80d6-2ae1-4591-a678-b86c698b07ff","year":2018},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:abd97a40e0b99f3d1b152db23f7680bcbf7c1d708218478e55b0d265a37c0a6b","observation_id":"728bb3d8-c593-4be8-ae0b-1fea80f59c78","resolution":{"observed_at":"2026-05-24T21:45:01.113038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hierarchical Attention Networks for Document Classification","venue":null,"work_id":"d6ae5fb5-e570-4bce-a0b9-808196197fda","year":2016},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:47bd30e675a9a8f8da41519eccb8f732869791026f526b6f2487410cb7d942c1","observation_id":"4444983c-48f4-4247-850c-0eea4417234f","resolution":{"observed_at":"2026-05-24T21:45:01.047196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Embedded Textual Content for Document Image Classification with CNNs","venue":null,"work_id":"5066922a-83a3-404e-a4a8-a63133762a31","year":2016},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:471727c659ea4a3ef42939d25235072b68c7504d03652066837818aa36bc475e","observation_id":"b0437f7d-6f6b-424a-bfe7-7b04bff4885d","resolution":{"observed_at":"2026-05-24T21:45:01.051065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning to Extract Semantic Structure from Documents Using Multimodal FCNNs","venue":null,"work_id":"5b090d42-e7f9-4bd3-8296-d162f810725c","year":2017},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:746901129d1cd6454f2ab5e44dbc00fb466f1388ccc08331273c93a7e6300c67","observation_id":"d1385c50-c2b8-491e-b190-619ec6b2dd87","resolution":{"observed_at":"2026-05-24T21:45:01.076382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Improving Classification of an Industrial Document Image Database by Combining Visual and Textual Features","venue":null,"work_id":"ca9a4d9c-2392-4c9f-8fe9-39491158d188","year":2014},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:9b11060cec477b472ca4946251b2f82982b1e4cf025c6db3768f3ade09afb0b4","observation_id":"43ac49cc-0c91-480f-b3c1-4e1f8ab9b672","resolution":{"observed_at":"2026-05-24T21:45:01.034617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"MobileNetV2: Inverted Residuals and Linear Bottlenecks","venue":null,"work_id":"05854234-a9cc-4572-acaa-6ed0027f5f4b","year":2018},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:39609c7842883c18dd44a38c59712bca05817aaa2d9433cb5b702e63971ffce4","observation_id":"702aecf6-511c-4e47-af4f-399a1f674a0f","resolution":{"observed_at":"2026-05-24T21:45:01.023215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"CNN Features Off-the-Shelf: An Astounding Baseline for Recognition","venue":null,"work_id":"9adff6fd-d9ad-44dc-9358-b90039f831c3","year":2014},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:6501c81c414b7f066bca8f4a76f5ae9703a8f6ccfdf09bc8a19e7d0a2be9de2a","observation_id":"89583378-a67a-469a-a32e-ac37f43f0486","resolution":{"observed_at":"2026-05-24T21:45:01.026925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep Residual Learning for Image Recognition","venue":null,"work_id":"bdf777ed-9521-43a3-ab55-021e6e3f1d3b","year":2016},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:8f84bb7d4ea0d6bb43a5cecf1a198f06d0e2b08058405dbc941dd0caf428f370","observation_id":"1a0f3465-ebae-4a3a-abec-68892d2f024e","resolution":{"observed_at":"2026-05-24T21:45:01.030786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A Threshold Selection Method from Gray-Level Histograms","venue":null,"work_id":"2119fd8f-735d-4f70-842b-09b791536b2b","year":1979},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:b59932ebc90bb690bedea431430a126671e95d3e76de74a6af22fe0d019750c6","observation_id":"50da01c9-6cb9-45bf-8dfa-95b1b2cd3566","resolution":{"observed_at":"2026-05-24T21:45:01.088159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Glove: Global V ectors for W ord Representation","venue":null,"work_id":"cca3c185-ce89-42c1-a45e-2e3661c4a0a7","year":2014},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:5d69c39251ebd7fa101613316ad3828287a0d99e0797c6c15496045873ca1868","observation_id":"639a8c39-f737-4d56-b164-2fa94fb8e0ea","resolution":{"observed_at":"2026-05-24T21:45:01.102903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mimicking W ord Embeddings using Subword RNNs","venue":null,"work_id":"ccd9f329-4960-44e2-8bc3-1dd4336e02f2","year":2017},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:6f3767a75806a19db40caa950084dd4f47482baaa90727dc12961d63b6885d44","observation_id":"690c46f3-db6d-4321-9fad-e78fbd42849b","resolution":{"observed_at":"2026-05-24T21:45:01.144076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Enriching W ord V ectors with Subword Information","venue":null,"work_id":"d5eff5ec-2637-47b4-b7da-c8a87e642799","year":2017},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:e734d3957c6a0ac8a9776f51875470537032178a9cf9618f2191505924cc8110","observation_id":"909ed0d1-bac0-4840-8dd1-744aa625a704","resolution":{"observed_at":"2026-05-24T21:45:01.003469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Bag of Tricks for Efficient T ext Classification","venue":null,"work_id":"6f8d3c34-b3b3-4223-9a64-49053b4716f3","year":2017},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:34b39cb87c0c8659ae8c1bfae50b6630465906e5722afcc2b1d4e69e25ca24db","observation_id":"78bbeede-d7bf-48dc-b468-7c881086080d","resolution":{"observed_at":"2026-05-24T21:45:00.998812Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Magnitude: A Fast, Efficient Universal V ector Embedding Utility Package","venue":null,"work_id":"e5036b76-5403-4ffd-82ec-1b09640e4461","year":2018},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:e87cba5d3776410d873d07b35d2af257582542f652a52e326c49edbf766a82cc","observation_id":"3e348398-7aa3-44be-8aac-bb0617b90532","resolution":{"observed_at":"2026-05-24T21:45:01.009076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A Simple but T ough-to-Beat Baseline for Sentence Embeddings","venue":null,"work_id":"e14c68f9-a3b5-41cd-b44b-335e02b1e6b9","year":2016},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:eb6587d0c7071a6673f9fd898ee1f9b6a78973e3627def60c7c3465afb642957","observation_id":"ad86258e-274c-4d12-9395-7936885f6ec8","resolution":{"observed_at":"2026-05-24T21:45:01.015243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"spaCy 2: Natural language understanding with Bloom embeddings, convolutional neural networks and incremental parsing","venue":null,"work_id":"22dfd02b-2dca-4d62-9a28-513eb763f3ab","year":2017},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:410d05594b657bf8c4ce5c871bbbadae112d25b9c1c1119ad2d1cfefe295dc45","observation_id":"6da6105f-4c77-4059-b83e-6b0b51d0596c","resolution":{"observed_at":"2026-05-24T21:45:00.992380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multimodal deep learning for robust RGB-D object recognition","venue":null,"work_id":"c89ba03b-a3bb-431a-8d7c-5625d1a48258","year":2015},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:b68636ce8ce4df271451e24acb4ea103386887124cb5711e84dd615784076524","observation_id":"9ea8a753-70ad-4d11-a956-4c21208b5316","resolution":{"observed_at":"2026-05-24T21:45:01.116513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Delving Deep into Rectifiers","venue":null,"work_id":"ff468270-d570-447f-bbfd-84a9e630c2ab","year":2015},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:6c251dbcb4e2992ee57d7c64dca8e025382bd2c61da4c1c27597e1f6c9a04280","observation_id":"fcb91b22-c817-446d-8dc1-e1aff7cdf5bd","resolution":{"observed_at":"2026-05-24T21:45:01.132006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Convolutional Neural Networks for Sentence Classification","venue":null,"work_id":"52c9cf87-c280-424e-9cc8-8781944831a1","year":2014},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:f7df3ea1c046d5c79a46c01de8ad2996104fcb4e2209fce859e0c7832d3208df","observation_id":"275cd81b-c655-4db4-bdfe-c3bf518081dc","resolution":{"observed_at":"2026-05-24T21:45:01.128391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Nielsen, Usability Engineering","venue":null,"work_id":"e57269d0-d99b-4261-8e8c-292340903187","year":1993},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:7e52feb766b30a7eaa344c1fd79c810367f440b0e6189951f7f76e000a79f649","observation_id":"207a73e0-08df-4415-a4f4-6128d6f1b57a","resolution":{"observed_at":"2026-05-24T21:45:01.106140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Xception: Deep Learning with Depthwise Separable Convolutions","venue":null,"work_id":"913404dd-3985-4af0-87dc-c8acdebcf1c1","year":2017},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:9f0216d53c382adfbc4f7e96d62940751b35b1bf93df431d2e1fd4b9cb65f9c2","observation_id":"91db809d-807d-499c-b5b4-8a171ee036f6","resolution":{"observed_at":"2026-05-24T21:45:01.038938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Robust W ord V ectors: Context-Informed Embeddings for Noisy T exts","venue":null,"work_id":"f9829231-756e-46c6-9283-588c6c37c99e","year":2018},"citing_paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-24T21:42:20.194268Z"},"links":{"citing_paper":"/paper/1907.06370"},"observation_digest":"sha256:36d5fcd30760631afe3a57728d18ace4d602a818cf669af7892372adfe9923da","observation_id":"e31bdd73-6a2d-4f65-8b4a-54b5c3399e93","resolution":{"observed_at":"2026-05-24T21:45:01.062052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1907.06370","last_updated":"2019-07-15T08:43:49Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T07:39:29.967587Z","submitted_at":"2019-07-15T08:43:49Z","title":"Multimodal deep networks for text and image-based document classification"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":39},"total_outbound_references":39},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 2 inbound Pith citation observations for arXiv:1907.06370."}