{"as_of":"2026-08-10T05:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e0b4ce66ee08807dc44602bbf8b518a79f66d335a5a6ac558f568a39446a31ae","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:39:11.182787Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.10084/citation-record","integrity":"/paper/2506.10084/integrity","json":"/paper/2506.10084/citation-record.json","paper":"/paper/2506.10084"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:19.353322Z","title":"Drop an octave: Reducing spatial redundancy in convolutional neural networks with octave convolution,","venue":null,"work_id":"52923c38-6033-4c5f-ab29-2a2a28a0031e","year":2019},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:03.571367Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:7ca0c809cec257709a414e5d90168236256a31db6023d1c70bcedca713fa2679","observation_id":"806d8e47-d208-41e3-b838-7bb9ca2bad95","resolution":{"observed_at":"2026-08-07T04:39:19.501239Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:03.687786Z","title":"Xception: Deep learning with depthwise separable convolutions,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:03.687786Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:dfb0a9719ca8b6032d7356eef76f12edb30becbd15ef7fdacebcc55042f46d78","observation_id":"a9794475-dbfe-4b0d-8dd0-006ce61849c8","resolution":{"observed_at":"2026-08-07T04:39:03.687786Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:19.146243Z","title":"Tackling multipath and biased training data for imu-assisted ble proximity detection,","venue":null,"work_id":"bc241dc9-49b3-4b5c-9efa-79748a979341","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:03.757498Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:2cc729c6387c8daa6d611d7f797044d15019a9c136c38aca97bb7cdbc2161934","observation_id":"0ea55165-17df-42bf-a97a-dbd5c9311287","resolution":{"observed_at":"2026-08-07T04:39:19.223560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:18.974484Z","title":"Micronet: Improving image recognition with extremely low flops,","venue":null,"work_id":"6b895cd0-a23a-48fb-8d1c-87ea727a3b85","year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:03.894309Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:f73ac73fd9c27abc75549087f7552db2c2df7e9bdc0cf9a6413da484cec8f92f","observation_id":"c49b8fdb-2678-4aad-99a5-bdc35f3f7ca6","resolution":{"observed_at":"2026-08-07T04:39:19.039135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1403.1687","last_updated":"2014-03-07T08:57:12Z","snapshot_observed_at":"2026-07-06T03:37:50.799760Z","submitted_at":"2014-03-07T08:57:12Z","title":"Rigid-Motion Scattering for Texture Classification","version":1},"cited_work":{"arxiv_id":"1403.1687","doi":null,"metadata_source":"pith","pith_arxiv_id":"1403.1687","snapshot_observed_at":"2026-08-07T04:39:12.608456Z","title":"Rigid-Motion Scattering for Texture Classification","venue":"cs.CV","work_id":"91900317-c703-47da-a10e-d59fe9cc836f","year":2014},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:03.985028Z"},"links":{"cited_paper":"/paper/1403.1687","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:ea4fd350962b2488b6dcd04d95811e3466d041c0d7cee95dfa22a39f018eacc6","observation_id":"e8c588ec-9bef-4146-980e-6821661967db","resolution":{"observed_at":"2026-08-07T04:39:12.702802Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:18.720816Z","title":"Hetconv: Heterogeneous kernel-based convolutions for deep cnns,","venue":null,"work_id":"e03c25be-62aa-4078-ac06-bf2e58c6868d","year":2019},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:04.096176Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:20b1bf1ff0dfd0e41b054504a9dd1105f0191d88a4588a278a2901b71c8aee16","observation_id":"3f20b818-ae39-48ef-84ed-c9f02be9b078","resolution":{"observed_at":"2026-08-07T04:39:18.817731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-10T01:12:16.468283Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-07T04:39:04.248901Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:04.248901Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:e4fba10f5ffdaf7ca5dccf6057532f4b99f246f8b575aad69dfa84c069f8504f","observation_id":"d74de223-2c67-4adb-9d3a-49a4af2cd77d","resolution":{"observed_at":"2026-08-07T04:39:04.248901Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:18.524223Z","title":"Training data-efficient image transformers & distillation through attention,","venue":null,"work_id":"0a6a3811-a857-4b84-8781-d9165304ee81","year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:04.353431Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:20ad5adf2148f6c432397258f1c06fa832c88ebbcc90af1f2643f0d2f38d6c5e","observation_id":"d48247c5-4d8f-4b28-bf79-41002e3eaf69","resolution":{"observed_at":"2026-08-07T04:39:18.622808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:18.275887Z","title":"A depth-first search-based algorithm for the minimization of the largest connected component in networks,","venue":null,"work_id":"e190d7e5-f4fb-4079-ace9-2b99a3cf8b99","year":2023},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:04.466102Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:ee3a3b37c597e63258aab86b604d750643f3dd53ddd9a21a6d341370d80affc7","observation_id":"53181714-b549-4a03-b34e-01e58c5f5866","resolution":{"observed_at":"2026-08-07T04:39:18.380210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:18.019523Z","title":"Interleaved group convolutions,","venue":null,"work_id":"c2b0eb6d-d258-4af8-bce6-20650bbdf6cb","year":2017},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:04.555569Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:4926e4bedc5c7e11e9a3eab4b72770dcb33fff13070d0ea290f53c6601da784f","observation_id":"363480b2-1913-4e35-87fe-d33a344f4322","resolution":{"observed_at":"2026-08-07T04:39:18.143748Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07889","last_updated":"2023-03-09T04:43:38Z","snapshot_observed_at":"2026-08-10T04:58:47.271553Z","submitted_at":"2022-10-14T15:14:26Z","title":"Semi-supervised Learning with Network Embedding on Ambient RF Signals for Geofencing Services","version":2},"cited_work":{"arxiv_id":"2210.07889","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.07889","snapshot_observed_at":"2026-08-07T04:39:12.279901Z","title":"Semi-supervised Learning with Network Embedding on Ambient RF Signals for Geofencing Services","venue":"cs.NI","work_id":"5f7468cf-4a80-48e8-847e-c01eea7a8651","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:04.648261Z"},"links":{"cited_paper":"/paper/2210.07889","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:296ed909524ef451d084355d5fb6a171c6c2e078b824455fccc5e9b9de957533","observation_id":"a32bc01e-f695-4ae1-8013-67f02ca96c2d","resolution":{"observed_at":"2026-08-07T04:39:12.469879Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:04.799316Z","title":"Imagenet classification with deep convolutional neural networks,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:04.799316Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:3484e9f8bf4b2b76a9ede9411a4349238c77f157ebf6638fb8d98de1242f6103","observation_id":"204a240c-1d3d-467e-b0c2-7a0cb5288928","resolution":{"observed_at":"2026-08-07T04:39:04.799316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:17.735537Z","title":"Searching for mobilenetv3,","venue":null,"work_id":"fad0851a-8d77-46f7-86d9-a0fc168d2b01","year":2019},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:04.907908Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:939a160a054f05943386381a98f6265e163cce68c38fc53481f86fc60047393c","observation_id":"ab41c3a3-f979-4411-81bb-cff459424df4","resolution":{"observed_at":"2026-08-07T04:39:17.835088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1704.04861","last_updated":"2017-04-17T03:57:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-04-17T03:57:34Z","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1704.04861","snapshot_observed_at":"2026-08-07T04:39:05.057417Z","title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:05.057417Z"},"links":{"cited_paper":"/paper/1704.04861","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:d08d028889f7d7adfbe2fe74a48779a56b5aee516d679ad8e13565f4de40ab3c","observation_id":"8898e184-204c-4b79-a254-a54fe6980702","resolution":{"observed_at":"2026-08-07T04:39:05.057417Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:05.193076Z","title":"Mobilenetv2: Inverted residuals and linear bottlenecks,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:05.193076Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:2ad67d3285b0b449730df43c082b2028e6e012ff9b08a1e3f93a2bf26a193ebd","observation_id":"105c30a2-3fc9-4a92-b74a-a17f173e3e1c","resolution":{"observed_at":"2026-08-07T04:39:05.193076Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:05.265661Z","title":"Shufflenet v2: Practical guidelines for efficient cnn architecture design,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:05.265661Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:b4ae637e9be8b98448b44d02f89f503361edf84a35e4093289b3b9eb93e1de6c","observation_id":"8a7718d3-4ee5-4016-b8b5-e0c741e0f250","resolution":{"observed_at":"2026-08-07T04:39:05.265661Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:17.488761Z","title":"Shufflenet: An extremely efficient convolutional neural network for mobile devices,","venue":null,"work_id":"37800457-2b4b-49a6-b293-db3f4cc4563c","year":2018},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:05.355811Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:fb69f53448af522fc0443e16ffb0d173e90615788cddc91ee6fde0387826d7b4","observation_id":"7a2a274a-5149-4f3a-8051-ae92b0c3f617","resolution":{"observed_at":"2026-08-07T04:39:17.557678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:17.271000Z","title":"Ghostnet: More features from cheap operations,","venue":null,"work_id":"846a5c3d-1094-466c-876c-7be59b714a6c","year":2020},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:05.492585Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:27687d85f80ab874c8a450f9138343976cbe7ce8a8f5b20b8087444f1f4d337a","observation_id":"96829a3a-f280-45ea-8857-b9fea6ad9375","resolution":{"observed_at":"2026-08-07T04:39:17.372297Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:05.639861Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:05.639861Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:a30837a2cf126d70ea4fbcceaf2c0d521b6bb7fd9a1c5de3ff9a216137a448ef","observation_id":"e65c9664-4b9b-4f58-aa9f-e75110421d9b","resolution":{"observed_at":"2026-08-07T04:39:05.639861Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:17.058850Z","title":"Condensenet: An efficient densenet using learned group convolutions,","venue":null,"work_id":"8158990f-1654-4f38-a934-741fb13c96d4","year":2018},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:05.766394Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:3785f0caea73efaccb30ead33e553be8f35443c523f9fe7f86167ded9ea1e766","observation_id":"ca73c324-7d39-4e9c-ad1d-c045698fe329","resolution":{"observed_at":"2026-08-07T04:39:17.156456Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:05.896239Z","title":"Efficientnetv2: Smaller models and faster training,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:05.896239Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:370841e33d79d6c8dfed8f6cc90623744bce03712afa3350e8eba489d48599b1","observation_id":"1244ce0f-29ce-411d-b220-514fca735249","resolution":{"observed_at":"2026-08-07T04:39:05.896239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:16.821100Z","title":"Run, don’t walk: Chasing higher FLOPS for faster neural networks,","venue":null,"work_id":"d7f1b622-427b-48b1-8dfc-aefb683ccf6b","year":2023},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:06.007090Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:fe7fb839e7c09480016f28f49416eb517d5fd83dc7cf60b428217a072472b6a1","observation_id":"29746ca6-251a-4b66-bff0-cba44372ed10","resolution":{"observed_at":"2026-08-07T04:39:16.950170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:16.631193Z","title":"Rewrite the stars,","venue":null,"work_id":"aaeea559-0564-47b6-b681-89b3bd451465","year":2024},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:06.141971Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:cb7ab2d32cb760197844c0c20243163d7858a6e5f8d1d153bb4a31c0adcb5f91","observation_id":"476f1628-b234-4ec6-a41b-08afb167e9ad","resolution":{"observed_at":"2026-08-07T04:39:16.728524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:06.259053Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:06.259053Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:9dbd00c5c329fb3a82aaab2511ac4db7181740182b4b0626075db6213c53072e","observation_id":"de7238f1-fe82-4a54-812b-b7a23b190241","resolution":{"observed_at":"2026-08-07T04:39:06.259053Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:16.412202Z","title":"Social ode: Multi-agent trajectory forecasting with neural ordinary differential equations,","venue":null,"work_id":"a7871b58-5880-406b-bfbf-0e01708f540f","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:06.427482Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:66458f92622ae407c08c0552eb52bb5b39eac1be4ac4a8376da38532326ec310","observation_id":"578007ab-ceb0-4bd9-9ffc-b962d17532de","resolution":{"observed_at":"2026-08-07T04:39:16.512066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.10270","last_updated":"2022-06-23T10:51:04Z","snapshot_observed_at":"2026-08-06T08:18:31.112514Z","submitted_at":"2021-06-18T17:58:20Z","title":"How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.10270","snapshot_observed_at":"2026-08-07T04:39:06.578252Z","title":"How to train your vit? data, augmentation, and regularization in vision transformers,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:06.578252Z"},"links":{"cited_paper":"/paper/2106.10270","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:495fc1d34434f6a7988ec5bc55dc3ab092ff439a3b5e8febf29e24ede12919f4","observation_id":"f3e75e37-b0af-4a03-8caf-d19a2825939c","resolution":{"observed_at":"2026-08-07T04:39:06.578252Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.07118","last_updated":"2022-04-14T17:13:44Z","snapshot_observed_at":"2026-08-02T11:55:13.359532Z","submitted_at":"2022-04-14T17:13:44Z","title":"DeiT III: Revenge of the ViT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.07118","snapshot_observed_at":"2026-08-07T04:39:06.764672Z","title":"Deit iii: Revenge of the vit,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:06.764672Z"},"links":{"cited_paper":"/paper/2204.07118","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:bd7515e42d27494455fd74f5b0e8868fbf08aa2df95fc8593aefefaeae28814e","observation_id":"70dc64a6-ebba-4301-8da2-f96756616281","resolution":{"observed_at":"2026-08-07T04:39:06.764672Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:16.162306Z","title":"Levit: a vision transformer in convnet’s clothing for faster inference,","venue":null,"work_id":"15f54c71-b114-4c83-8ead-00dde842be57","year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:06.874404Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:ad80f4893697e2762cff1a31872f8f344c774183d5440aba144fdfe83ecc92a0","observation_id":"a7facae7-7179-412d-aaf1-193aac658bdf","resolution":{"observed_at":"2026-08-07T04:39:16.278539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:15.990584Z","title":"Swin transformer v2: Scaling up capacity and resolution,","venue":null,"work_id":"d6a9aad7-d9bc-4591-95d4-843b38327d16","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:07.049031Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:87b2f019cff7577eb0970a346bd5021795f7490d5fd6f36b7325c22fda46f625","observation_id":"0dadef36-4131-4e45-93f6-d65774d4a2ce","resolution":{"observed_at":"2026-08-07T04:39:16.045620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:07.186043Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:07.186043Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:450cfd6a3c04afed03c53b20831869b4aa7ebab3a93b8ffa6ccea8c0c63fe639","observation_id":"8666fb80-fab3-4fb9-95e0-50a9932de344","resolution":{"observed_at":"2026-08-07T04:39:07.186043Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:07.300489Z","title":"Pyramid vision transformer: A versatile backbone for dense prediction without convolutions,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:07.300489Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:2ebd6af891d5068d856f15d8a867b6f592aaa29ae425ce19c4f1482855193e31","observation_id":"a228e0e5-ee26-42a9-862b-d9f8f75c78ff","resolution":{"observed_at":"2026-08-07T04:39:07.300489Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:15.653604Z","title":"A tree-based structure-aware transformer decoder for image-to-markup generation,","venue":null,"work_id":"2e6a377a-f831-4b7c-a2a0-1e1dfa66a3b1","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:07.438359Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:cd34db2e06ac17cfe5450dfa90c1d34d523dcd7bc484fdceb9295d47a5fb7820","observation_id":"33c6d456-774f-4274-a9f7-2039309d2d0a","resolution":{"observed_at":"2026-08-07T04:39:15.837452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:15.456488Z","title":"Xcit: Cross-covariance image transformers,","venue":null,"work_id":"539e9e05-4bd4-4dc5-b86c-76501e4920d6","year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:07.609803Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:a5b1b9ef5401293b1cdef0669c59f5a17dd9b111785c3a50396c6cc8f939c6c4","observation_id":"1ec2a9c0-e65c-4fbd-9b49-49701206e506","resolution":{"observed_at":"2026-08-07T04:39:15.549441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2207.05557","last_updated":"2022-07-12T14:27:57Z","snapshot_observed_at":"2026-07-06T13:30:25.055070Z","submitted_at":"2022-07-12T14:27:57Z","title":"LightViT: Towards Light-Weight Convolution-Free Vision Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.05557","snapshot_observed_at":"2026-08-07T04:39:07.776403Z","title":"Lightvit: Towards light-weight convolution-free vision transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:07.776403Z"},"links":{"cited_paper":"/paper/2207.05557","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:e239d425049b4e7e5925159244d404477c5fa07786c114b26cc64e162b4f8c6d","observation_id":"cb63ece0-2404-4a42-b679-73dab271b776","resolution":{"observed_at":"2026-08-07T04:39:07.776403Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:15.230813Z","title":"Soft: Softmax-free transformer with linear complexity,","venue":null,"work_id":"2a2e3cd4-6760-420f-becb-be9ccfadcf09","year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:07.991100Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:b46f9c62ef4de854dc972abec91c3b118fb8ea5eadeb1cacfdb4e2ef32de5058","observation_id":"5a2878f0-a64b-490f-b219-3f0d79c59a30","resolution":{"observed_at":"2026-08-07T04:39:15.344339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.02767","last_updated":"2022-03-23T19:10:58Z","snapshot_observed_at":"2026-08-09T10:52:21.435615Z","submitted_at":"2022-01-08T05:45:32Z","title":"QuadTree Attention for Vision Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.02767","snapshot_observed_at":"2026-08-07T04:39:08.126990Z","title":"Quadtree attention for vision transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:08.126990Z"},"links":{"cited_paper":"/paper/2201.02767","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:eeaadc70aeedb32ac04f39a846d7aefbb80faa0a3ae4159e81dace27b6ad40d6","observation_id":"fc1c2a2c-2a17-405a-942f-831a1d2fccc5","resolution":{"observed_at":"2026-08-07T04:39:08.126990Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:14.933800Z","title":"Scaling local self-attention for parameter efficient visual backbones,","venue":null,"work_id":"ea2ff97f-4463-4034-99dd-97e109d08a3f","year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:08.296312Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:335c264cb98b28913ff0ee67cd728d432b041a1cdc2bc4c3e45f8f7834b3cfd8","observation_id":"16d68f75-f183-4c73-8c1e-292a2c3492e2","resolution":{"observed_at":"2026-08-07T04:39:15.036834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:14.644671Z","title":"Mobileformer: Bridging mobilenet and transformer,","venue":null,"work_id":"501b7c5d-1946-4804-a186-0900d1b9ed58","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:08.432636Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:a9a5d245ef683fc93735dd901435facb215ecc62be1006d317bdc4a01aa8c5cd","observation_id":"b89320f5-7f1e-4547-bc20-fb7afe4f1696","resolution":{"observed_at":"2026-08-07T04:39:14.797926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:14.413361Z","title":"Coatnet: Marrying convolution and attention for all data sizes,","venue":null,"work_id":"2e3b0795-c1dc-40f2-92cb-8d190b2cf6c7","year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:08.522913Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:13d503247b5fd7ce7843505c3b4707fd422eec1debdeb359617640d18486dc32","observation_id":"2e7ebdf1-c6a2-4aa4-a185-48e40591ec7b","resolution":{"observed_at":"2026-08-07T04:39:14.536225Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:08.626938Z","title":"Bottleneck transformers for visual recognition,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:08.626938Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:39a634124e57ce61a09b20f8bcde36dbf78a5f09e3871c2931937def13f107e0","observation_id":"e5547e08-0683-437c-828e-0527a945c6b6","resolution":{"observed_at":"2026-08-07T04:39:08.626938Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.14756","last_updated":"2024-02-06T02:57:35Z","snapshot_observed_at":"2026-08-04T16:41:46.813009Z","submitted_at":"2022-05-29T20:07:23Z","title":"EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense Prediction","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.14756","snapshot_observed_at":"2026-08-07T04:39:08.739752Z","title":"Efficientvit: Enhanced linear attention for high-resolution low-computation visual recognition,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:08.739752Z"},"links":{"cited_paper":"/paper/2205.14756","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:f11b031c604736f8edf6505e2d1e5f78858054dbc72c9f8198a3261714d9b925","observation_id":"da2c2845-d02a-4876-9e7f-fd817e9bc5c3","resolution":{"observed_at":"2026-08-07T04:39:08.739752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.01191","last_updated":"2022-10-11T03:06:16Z","snapshot_observed_at":"2026-08-10T05:17:06.462208Z","submitted_at":"2022-06-02T17:51:03Z","title":"EfficientFormer: Vision Transformers at MobileNet Speed","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.01191","snapshot_observed_at":"2026-08-07T04:39:08.867481Z","title":"Efficientformer: Vision transformers at mobilenet speed,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:08.867481Z"},"links":{"cited_paper":"/paper/2206.01191","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:5e5557e8ee6581f6c921e683d334dd7380d869a9c37bf654341290f1e142373c","observation_id":"b8be29fa-054c-4bb4-a88e-81d400880e4f","resolution":{"observed_at":"2026-08-07T04:39:08.867481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.02680","last_updated":"2022-06-06T15:31:35Z","snapshot_observed_at":"2026-08-03T05:32:57.281028Z","submitted_at":"2022-06-06T15:31:35Z","title":"Separable Self-attention for Mobile Vision Transformers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.02680","snapshot_observed_at":"2026-08-07T04:39:08.980998Z","title":"Separable self-attention for mobile vision transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:08.980998Z"},"links":{"cited_paper":"/paper/2206.02680","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:a749c6603cfa6c2c21055f00cd7cda5d481d217dcd577be733e25163920307ec","observation_id":"add36f08-bf81-4b26-85e5-b8f7e260b0b7","resolution":{"observed_at":"2026-08-07T04:39:08.980998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.03436","last_updated":"2022-07-21T21:54:49Z","snapshot_observed_at":"2026-08-09T11:51:35.946870Z","submitted_at":"2022-05-06T18:17:19Z","title":"EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers","version":2},"cited_work":{"arxiv_id":"2205.03436","doi":null,"metadata_source":"pith","pith_arxiv_id":"2205.03436","snapshot_observed_at":"2026-08-07T04:39:11.963093Z","title":"EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers","venue":"cs.CV","work_id":"e2a8c7d1-6b65-411e-8560-90adccd6a422","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:09.135551Z"},"links":{"cited_paper":"/paper/2205.03436","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:f7b498f9ce8c359748565e59b8e6db867dd1156ecd48d5b37195c80fbf4c6799","observation_id":"376b15ef-3148-4f0b-92f9-c386b30537cd","resolution":{"observed_at":"2026-08-07T04:39:12.035090Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.10224","last_updated":"2022-03-18T08:45:29Z","snapshot_observed_at":"2026-08-08T08:30:35.914721Z","submitted_at":"2021-07-21T17:23:06Z","title":"CycleMLP: A MLP-like Architecture for Dense Prediction","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.10224","snapshot_observed_at":"2026-08-07T04:39:09.219446Z","title":"Cyclemlp: A mlp-like architecture for dense prediction,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:09.219446Z"},"links":{"cited_paper":"/paper/2107.10224","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:e110d8dcafd1ea319386292ca3346445787372f985806e4da64df6f4e6790740","observation_id":"b1ac31eb-bbaf-4ebb-aa67-b84c6f814494","resolution":{"observed_at":"2026-08-07T04:39:09.219446Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.08391","last_updated":"2022-03-17T06:59:03Z","snapshot_observed_at":"2026-07-06T11:30:03.281639Z","submitted_at":"2021-07-18T08:56:34Z","title":"AS-MLP: An Axial Shifted MLP Architecture for Vision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.08391","snapshot_observed_at":"2026-08-07T04:39:09.346061Z","title":"As-mlp: An axial shifted mlp architecture for vision,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:09.346061Z"},"links":{"cited_paper":"/paper/2107.08391","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:dd3f73fa417e542dfd4720200c9f27aecaf899a7c9fff87b168faa51bbb383f0","observation_id":"a609053e-ee6f-4cda-b4a5-fb144a050478","resolution":{"observed_at":"2026-08-07T04:39:09.346061Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:14.158945Z","title":"Mlp-mixer: An all-mlp architecture for vision,","venue":null,"work_id":"0da9f4d7-7bc1-4b36-810e-184b0d7eaa18","year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:09.506311Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:4cd98df4012ea87b3b4a431ab75bbb4e52fb2b65864c5f2952aadfa879da4e92","observation_id":"b7a86f5c-95df-45cd-96c9-01d0b0ece1da","resolution":{"observed_at":"2026-08-07T04:39:14.295030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:13.819244Z","title":"Are we ready for a new paradigm shift? a survey on visual deep mlp,","venue":null,"work_id":"c259eb3f-3cd0-4595-ad5e-4c77857bcf74","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:09.634113Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:e5a7d4ec2f8ede52936c5b21c42b3f1c0fb7140055d4cba8d3c8280f1e438005","observation_id":"f93c8576-a6b9-4469-8479-78528cb24b49","resolution":{"observed_at":"2026-08-07T04:39:13.978801Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:13.624055Z","title":"A convnet for the 2020s,","venue":null,"work_id":"b71d322c-bb01-4175-82dd-40b37554a31d","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:09.725049Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:7614c60c89b20d0c2c2cdc9364f755234e82d222f094c075a295f4347dd23f9b","observation_id":"52d47feb-e90b-4ae6-8d71-53906c5e2188","resolution":{"observed_at":"2026-08-07T04:39:13.697740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.10801","last_updated":"2022-01-26T08:17:06Z","snapshot_observed_at":"2026-08-08T22:27:51.548606Z","submitted_at":"2022-01-26T08:17:06Z","title":"When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism","version":1},"cited_work":{"arxiv_id":"2201.10801","doi":null,"metadata_source":"pith","pith_arxiv_id":"2201.10801","snapshot_observed_at":"2026-08-07T04:39:11.644895Z","title":"When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism","venue":"cs.CV","work_id":"a6d06e98-0de4-46bb-9096-2ddf1d2c5bec","year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:09.883037Z"},"links":{"cited_paper":"/paper/2201.10801","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:884fa8f511cfc44930f519cfb2cc2dbb8977973ae31f89de6be183b9a4de9100","observation_id":"fcbec2ac-5a05-42ef-9ed6-7c4135910e8b","resolution":{"observed_at":"2026-08-07T04:39:11.790921Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.02178","last_updated":"2022-03-04T17:17:31Z","snapshot_observed_at":"2026-07-06T11:54:38.041673Z","submitted_at":"2021-10-05T17:07:53Z","title":"MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.02178","snapshot_observed_at":"2026-08-07T04:39:09.982714Z","title":"Mobilevit: Light-weight, general-purpose, and mobile-friendly vision transformer,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:09.982714Z"},"links":{"cited_paper":"/paper/2110.02178","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:0e6abcdc7b69612f2cdfcd3ffaa499f762b0a4b2a9362a77d14275c9dfe54a13","observation_id":"5b19edc8-e875-4459-8f54-b46c22740a60","resolution":{"observed_at":"2026-08-07T04:39:09.982714Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.01261","last_updated":"2018-10-17T17:51:36Z","snapshot_observed_at":"2026-07-06T06:42:54.610341Z","submitted_at":"2018-06-04T17:58:18Z","title":"Relational inductive biases, deep learning, and graph networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.01261","snapshot_observed_at":"2026-08-07T04:39:10.066867Z","title":"Relational inductive biases, deep learning, and graph networks,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:10.066867Z"},"links":{"cited_paper":"/paper/1806.01261","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:c14fca93744c2ab1e6afe0a39486ed02bcc31c1e9e2ee17b3068c9dd17a7a745","observation_id":"7d194f86-138c-4d8c-9f07-e2ee74652a97","resolution":{"observed_at":"2026-08-07T04:39:10.066867Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:10.191112Z","title":"Learning fast approximations of sparse coding,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:10.191112Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:e13b2476c9d668f45d88fcf31b8bef6dbe111e5709e96a6b7fdbbd31c4b4f30e","observation_id":"d7332823-a5ae-4fd2-aff0-917958b6d56c","resolution":{"observed_at":"2026-08-07T04:39:10.191112Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:13.305239Z","title":"Neural execution of graph algorithms,","venue":null,"work_id":"522b585b-f181-424b-957f-fc7c16ab43ae","year":2019},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:10.333516Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:44b8c10e9ae2a8a7187e5a09838d393e93f108e8bc67c92e9b89a0ddce4e0e85","observation_id":"3df61d0f-e5a0-42c4-9af4-9b42dfde6da3","resolution":{"observed_at":"2026-08-07T04:39:13.448185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T04:39:13.053782Z","title":"Compositional attention networks for machine reasoning,","venue":null,"work_id":"369f56dc-9cec-4cb5-b7cc-b89cb2b4b8ae","year":2018},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:10.466359Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:5b271978fc6303d12f20c6aea7e49cca4de22642aaf14eddb99f35ced79200e8","observation_id":"8d0792c5-bf80-4c48-812c-10801ea6dc1d","resolution":{"observed_at":"2026-08-07T04:39:13.150582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.11903","last_updated":"2023-01-10T23:07:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-01-28T02:33:07Z","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.11903","snapshot_observed_at":"2026-08-07T04:39:10.610375Z","title":"Chain of thought prompting elicits reasoning in large language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:10.610375Z"},"links":{"cited_paper":"/paper/2201.11903","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:2c2bd40ebc6bc04076adeac1f02579be013a82c29bf43af61ec2b7624645baa8","observation_id":"060a362c-f2e1-4569-bf24-048c8638cbc4","resolution":{"observed_at":"2026-08-07T04:39:10.610375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10601","last_updated":"2023-12-03T22:50:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-17T23:16:17Z","title":"Tree of Thoughts: Deliberate Problem Solving with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10601","snapshot_observed_at":"2026-08-07T04:39:10.743589Z","title":"Tree of thoughts: Deliberate problem solving with large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:10.743589Z"},"links":{"cited_paper":"/paper/2305.10601","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:3e6319264f1c6308c5de14b7afabc1bd5ea36a9fdc0dc521796e866046e70bec","observation_id":"c72e8be9-2561-451f-9ee7-788ae2250630","resolution":{"observed_at":"2026-08-07T04:39:10.743589Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:12.817862Z","title":"This looks like that: deep learning for interpretable image recognition,","venue":null,"work_id":"e55bc97d-49e9-4e31-ac89-8bbda1a1a542","year":2019},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:10.918519Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:6e95fef76341900a7df7366b12998b5d01a99479e1af022304f45c50f9e127e2","observation_id":"40814b94-6e4e-47c3-97cf-b4f77b01b0ad","resolution":{"observed_at":"2026-08-07T04:39:12.957783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.07345","last_updated":"2022-07-26T13:43:51Z","snapshot_observed_at":"2026-08-07T10:40:15.284646Z","submitted_at":"2021-11-14T13:56:20Z","title":"On the Performance of the Depth First Search Algorithm in Supercritical Random Graphs","version":3},"cited_work":{"arxiv_id":"2111.07345","doi":null,"metadata_source":"pith","pith_arxiv_id":"2111.07345","snapshot_observed_at":"2026-08-07T04:39:11.345274Z","title":"On the Performance of the Depth First Search Algorithm in Supercritical Random Graphs","venue":"math.CO","work_id":"3af3fa73-e37b-426d-ac72-52c0e191102f","year":2021},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:11.035503Z"},"links":{"cited_paper":"/paper/2111.07345","citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:61f7df5e4e6f6d95c68b9913fbc1555ca734a11534068d04f65bc314dcc98ffa","observation_id":"dc03a394-0c50-4b91-bcaa-d7a4bb769658","resolution":{"observed_at":"2026-08-07T04:39:11.451753Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:39:11.182787Z","title":"Wide residual networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T04:39:11.182787Z"},"links":{"citing_paper":"/paper/2506.10084"},"observation_digest":"sha256:1f86ddb2f8a94aac68586f4a4b2618596eb2e585bcc6f5f8d07649014b02715e","observation_id":"fa19aaf5-5305-47da-a9eb-90ae8ece1ce1","resolution":{"observed_at":"2026-08-07T04:39:11.182787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.10084","last_updated":"2025-06-11T18:04:45Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T06:20:37.657963Z","submitted_at":"2025-06-11T18:04:45Z","title":"DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":27,"verified_exact":5,"verified_fuzzy":28},"total_outbound_references":60},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2506.10084."}