{"as_of":"2026-08-08T05:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c04c6bd5884ecdd2ac159793c2025ead607ac6a732a9ed883e9a05c438479ae9","coverage":[{"denominator":68,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":68,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T10:06:23.763542Z","state":"measured"},{"denominator":68,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":68,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2508.00592/citation-record","integrity":"/paper/2508.00592/integrity","json":"/paper/2508.00592/citation-record.json","paper":"/paper/2508.00592"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:26.725737Z","title":"TDAM: A Topic-Dependent Attention Model for Sentiment Analysis","venue":null,"work_id":"7f592a0a-da62-4fb9-8461-56bd58f5840e","year":2019},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.527715Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:0e9bf4780e4f43374e98f491800f0a2049511d6c55b89d2a8ad103e5bab1a49c","observation_id":"da0108b7-b71c-4b9d-82d2-70d947483212","resolution":{"observed_at":"2026-08-06T10:06:26.729044Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2022.emnlp-main.328","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:23.916211Z","title":"Learning Semantic Textual Similarity via Topic-informed Discrete Latent Variables","venue":null,"work_id":"418938d4-a3b0-4d70-ae81-7bf9e5af88b4","year":2022},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.531770Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:08ba8cd72f8791e4fa6aaa76b2ff32cfc30d33e3f8f9b241e8378720c4d1c5c1","observation_id":"3a3b5bbb-68e9-42b5-baf6-2fa5686c8fcb","resolution":{"observed_at":"2026-08-06T10:06:23.920014Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:27.003348Z","title":"Overview of the HASOC Track at FIRE 2024: Hate-Speech Identification in English and Bengali","venue":null,"work_id":"efe05449-ab50-4306-b9af-e47d063e9a66","year":2024},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.539077Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:8ec5ce4d5ba1588467f07fc91a3b312a3c2a553a449b3d2535e511b34fe08894","observation_id":"9d69335a-d167-4858-8ea0-2ec366c6e1bc","resolution":{"observed_at":"2026-08-06T10:06:27.006691Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:26.374046Z","title":"TOPIC MAP-BN: SCALABLE AND EXPLAINABLE FRAME- WORK FOR CROSS-SOURCE BANGLA NEWS RECOMMENDATION WITH BANGLABERT AND BERTOPIC","venue":null,"work_id":"9861b11b-6306-4b54-b647-a911721500bd","year":2025},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.542537Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:9d70ebfb79ee50533ee7748bbb733a56899961619fa43f1991c9520d8a1975a4","observation_id":"67a517d5-0122-4d8e-af1d-1342d62a63bd","resolution":{"observed_at":"2026-08-06T10:06:26.377217Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.993352Z","title":"Latent Dirichlet Allocation","venue":null,"work_id":"21a68966-a63f-4916-b58f-c9f865cf94b0","year":2003},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.546046Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:dad10b95c6c8a30c431601ffd5227bc1ad67decb66dda522f96fe4cc79a5e739","observation_id":"5b4806e1-6447-4057-ae97-263c405bf03c","resolution":{"observed_at":"2026-08-06T10:06:26.996371Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:23.549875Z","title":"Learning the parts of objects by non-negative matrix factorization","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.549875Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:69bba08cfd2a20c4982c9df1e81e118f63a189681ed28a3590eb98686e6fdcb0","observation_id":"07c6c7eb-8a75-44cf-bb83-6d9466084000","resolution":{"observed_at":"2026-08-06T10:06:23.549875Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1703.01488","last_updated":"2017-03-04T16:28:15Z","snapshot_observed_at":"2026-08-07T21:03:29.194887Z","submitted_at":"2017-03-04T16:28:15Z","title":"Autoencoding Variational Inference For Topic Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.01488","snapshot_observed_at":"2026-08-06T10:06:23.553133Z","title":"Autoencoding Variational Inference for Topic Models","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.553133Z"},"links":{"cited_paper":"/paper/1703.01488","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:3568c8ce3b0858afb0ccb02e0bebe20ed8c29b213c3b48601232e0bfba0696c9","observation_id":"764407a4-657f-4f35-97fd-99938e742538","resolution":{"observed_at":"2026-08-06T10:06:23.553133Z","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":"2026-08-06T10:06:26.983542Z","title":"Topic modeling in embedding spaces","venue":null,"work_id":"25a0e641-9cf9-498f-9aa4-e6b641e953b5","year":2020},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.556894Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:e32750197f01a82bba1d7f3952c25402bcfb78355693cee89082b44b340f6efa","observation_id":"eb18d4bc-26ac-473a-8550-cca145c968cb","resolution":{"observed_at":"2026-08-06T10:06:26.986929Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:23.560376Z","title":"Pre-trainingisaHotTopic: ContextualizedDocumentEmbeddingsImprove Topic Coherence","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.560376Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:0d8c3c9edc9611548fbb75f4a89a8cfdfdbbd909bbea17606369e621e210a8aa","observation_id":"e59ea3e7-3c84-449d-9ed7-72bcb9e57a1c","resolution":{"observed_at":"2026-08-06T10:06:23.560376Z","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":"2026-08-06T10:06:23.564330Z","title":"Cross-lingual Contextualized Topic Models with Zero- shot Learning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.564330Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:83d7de6d74da6b39ff9fbdc04fff0d3b1d661298086914daf3b36e05d73769ba","observation_id":"d7bf4de2-68b6-4ffb-b2d8-2d70571db9ed","resolution":{"observed_at":"2026-08-06T10:06:23.564330Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2008.09470","last_updated":"2020-08-19T20:58:27Z","snapshot_observed_at":"2026-07-06T09:49:07.122303Z","submitted_at":"2020-08-19T20:58:27Z","title":"Top2Vec: Distributed Representations of Topics","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.09470","snapshot_observed_at":"2026-08-06T10:06:23.567645Z","title":"Top2Vec: Distributed Representations of Topics","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.567645Z"},"links":{"cited_paper":"/paper/2008.09470","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:1447ea62c9cd023b2c015dee469ee76eb4b59222645caef5ca514b6eb05899fb","observation_id":"74a98a77-5248-4a9f-921a-c69ea169f654","resolution":{"observed_at":"2026-08-06T10:06:23.567645Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.05794","last_updated":"2022-03-11T08:35:15Z","snapshot_observed_at":"2026-07-06T12:46:41.057346Z","submitted_at":"2022-03-11T08:35:15Z","title":"BERTopic: Neural topic modeling with a class-based TF-IDF procedure","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.05794","snapshot_observed_at":"2026-08-06T10:06:23.571272Z","title":"BERTopic: Neural topic modeling with a class-based TF-IDF procedure","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.571272Z"},"links":{"cited_paper":"/paper/2203.05794","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:e8f7c52aaa76ce58d3dc678ae3389e7d35e08f12023e087f14ac02cceb82e100","observation_id":"a59345d9-39ea-4fdc-9eb3-e9187db90d1c","resolution":{"observed_at":"2026-08-06T10:06:23.571272Z","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":"2026-08-06T10:06:26.973678Z","title":"GraphBTM: Graph Enhanced Autoencoded Variational Inference for Biterm Topic Model","venue":null,"work_id":"9b207db5-6134-41ab-91fa-6d67642a13d7","year":2018},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.575624Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:d7c24dff623fa8d0aac2759f8dca745b701d84b2ca0d614170ba4142841a0ce0","observation_id":"9cc57c44-4f75-4616-a7c0-cced4b01e102","resolution":{"observed_at":"2026-08-06T10:06:26.977206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02078","last_updated":"2023-07-05T07:39:47Z","snapshot_observed_at":"2026-08-01T13:27:49.643402Z","submitted_at":"2023-07-05T07:39:47Z","title":"Graph Contrastive Topic Model","version":1},"cited_work":{"arxiv_id":"2307.02078","doi":null,"metadata_source":"pith","pith_arxiv_id":"2307.02078","snapshot_observed_at":"2026-08-06T10:06:26.195784Z","title":"Graph Contrastive Topic Model","venue":"cs.CL","work_id":"6dd451dc-0526-40ea-8dfd-42cc2bd8e25b","year":2023},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.579239Z"},"links":{"cited_paper":"/paper/2307.02078","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:cbc756c74a17adbe8df9959f4d1c074200f4d15e5c65829fd7695414742308bb","observation_id":"603ebc2e-2056-432d-82a1-6d6e6c62bfaa","resolution":{"observed_at":"2026-08-06T10:06:26.199515Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02115","last_updated":"2025-02-17T07:23:38Z","snapshot_observed_at":"2026-08-04T12:04:17.817938Z","submitted_at":"2024-04-02T17:18:48Z","title":"GINopic: Topic Modeling with Graph Isomorphism Network","version":3},"cited_work":{"arxiv_id":"2404.02115","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.02115","snapshot_observed_at":"2026-08-06T10:06:26.182250Z","title":"GINopic: Topic Modeling with Graph Isomorphism Network","venue":"cs.CL","work_id":"d45faf52-cfaa-4025-b542-4f46d4faeba1","year":2024},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.582924Z"},"links":{"cited_paper":"/paper/2404.02115","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:ff2dcbbefa11fbcd9cf0896d70246cfb79ae463d8a8e40e271ccbaaa981fd84e","observation_id":"b3197f1a-7cd9-4638-aa26-76fc89ea2190","resolution":{"observed_at":"2026-08-06T10:06:26.185966Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.963724Z","title":"Graph2topic: An opensource topic modeling framework based on sentence embedding and community detection","venue":null,"work_id":"1563a9cc-c608-4f9f-8ba9-ba06c9afce94","year":2023},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.586740Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:28ff13f974c3c0f3a18547dfa995a14b83f9306acd82a7155e12f4cd746affc9","observation_id":"7c2b5663-0b12-483f-9e1b-c6c3b92aec2d","resolution":{"observed_at":"2026-08-06T10:06:26.966959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.953693Z","title":"Topic Modeling Revisited: A Document Graph-based Neural Network Perspective","venue":null,"work_id":"adde5f0d-dbee-4e05-ab8b-e20489a4c1fb","year":2021},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.590438Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:34c6856f7476850e33b35bf8978cb14cbe036a8d65d1b7cc8721413255525129","observation_id":"195b343c-ef03-47e6-8262-f666341b4588","resolution":{"observed_at":"2026-08-06T10:06:26.957216Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:23.594703Z","title":"TopicGPT: A Prompt-based Topic Modeling Framework","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.594703Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:21d9dd0c92bbb063e2d52a347528bdb0109cb6f546a5cc7acd9783f5815e69fc","observation_id":"f341d1e2-981d-4752-9dd0-b6855dbded1f","resolution":{"observed_at":"2026-08-06T10:06:23.594703Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-06T10:06:26.940948Z","title":"Ethnologue: Languages of the World – Bengali; 2025","venue":null,"work_id":"ab95fdac-6d21-4441-9731-68a4fbffbfdc","year":2025},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.598170Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:cd5a2157adf7f22c492804316195164fe711b1e70b3cfaf53b9731255cc41a2b","observation_id":"d0f7ad73-a945-4662-8a83-7db2f893deb6","resolution":{"observed_at":"2026-08-06T10:06:26.945018Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"publication/3286411","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:26.166876Z","title":"Topic Modelling in Bangla Language: An LDA Approach to Optimize Topics and News Classification","venue":null,"work_id":"e7244263-dec9-4a2e-aa56-dc18dd22c797","year":2018},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.601418Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:0b59633fee606467975c3f15772eac17ae2161c964865176743673e0d54f2c0e","observation_id":"6ea03859-23b3-40ac-b0b7-857bc2236474","resolution":{"observed_at":"2026-08-06T10:06:26.172383Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5120/ijca2019919754","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:23.880777Z","title":"LDA2Vec: Combining LDA and Word2Vec for Topic Mod- eling in Bangla","venue":null,"work_id":"9fb13af7-3608-4c01-bd39-d2156c9e3956","year":2019},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.604655Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:2baff5435f52eb62a06fbf6d25a676d930f3a3941b6bcbfbb5f5a542ca8fd6ac","observation_id":"19603456-42a5-4e7a-bdd5-be28b96636b2","resolution":{"observed_at":"2026-08-06T10:06:23.884027Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5120/ijca2020920000","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:23.870270Z","title":"Topic Modeling and Trend Analysis of Bengali News Articles","venue":null,"work_id":"cafc31fe-00c7-4d3e-8044-1925031ce01c","year":2020},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.608016Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:d63766fbcdd79dbdb174122f7ceb1015db049387c824f63eeacb98b9ad0a09b9","observation_id":"439ef77f-e955-4c17-b686-b501d14bd4df","resolution":{"observed_at":"2026-08-06T10:06:23.874254Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"publication/3887797","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:26.051740Z","title":"Combining BERT with LDA: Improved Topic Mod- eling in Bengali Language","venue":null,"work_id":"aa379ca1-0244-43a6-8387-008efed0e78b","year":2025},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.611458Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:77d3f63702733b8324b1bf204b3b909f5e31728de01b5d65c2e2071493a8eda0","observation_id":"df2d4b89-b780-4781-a324-35ccbca67161","resolution":{"observed_at":"2026-08-06T10:06:26.057072Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.931047Z","title":"Likelihood Corpus Distribution: A Dirichlet-Polynomial Clustering Model for Bengali Topic Modeling","venue":null,"work_id":"f8641993-dc5a-4983-8a4b-1b468ee101eb","year":2024},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.614799Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:89810a46dee3f42348957f00030dd544c2a62488b87b8f35fa13229377787cef","observation_id":"f48312ec-25b4-4c3c-a8d6-7c82e3503f07","resolution":{"observed_at":"2026-08-06T10:06:26.934417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.920899Z","title":"Clustering LLM-based Word Embeddings to Determine Topics from Bangla Articles","venue":null,"work_id":"13a8f2f9-60cb-49e0-9dbd-48f4f7a78cd2","year":2025},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.617858Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:b7ca113a3e332ae8c14520a1fb4853d18684cfc3870362e0b4d492127d330ca5","observation_id":"f44087b7-0abd-4d02-add6-87fbfabc8ae2","resolution":{"observed_at":"2026-08-06T10:06:26.924457Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.09389","last_updated":"2022-10-17T19:37:42Z","snapshot_observed_at":"2026-07-06T14:06:52.447463Z","submitted_at":"2022-10-17T19:37:42Z","title":"Potrika: Raw and Balanced Newspaper Datasets in the Bangla Language with Eight Topics and Five Attributes","version":1},"cited_work":{"arxiv_id":"2210.09389","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.09389","snapshot_observed_at":"2026-08-06T10:06:25.832958Z","title":"Potrika: Raw and Balanced Newspaper Datasets in the Bangla Language with Eight Topics and Five Attributes","venue":"cs.CL","work_id":"3927b289-559c-4572-a7c4-cca379c8bf39","year":2022},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.621661Z"},"links":{"cited_paper":"/paper/2210.09389","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:3c4ed48930e5ea0ee735e4b3bac314595ca230cecf906705164bcfb52c315f1f","observation_id":"2ffa7e37-a1b8-447d-ae69-cebf302b821a","resolution":{"observed_at":"2026-08-06T10:06:25.836723Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2023.eacl-main.4","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:23.860520Z","title":"Shironaam: Bengali News Headline Generation using Auxiliary Information","venue":null,"work_id":"98e7fc50-f3a2-4b4e-b4f7-7c149a64e6bd","year":2023},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.625269Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:d0dc56aeeed776e0b6fc9c54c9c0dcb2fefca52e6166ec63edf57cc49d535f70","observation_id":"4987454c-d4be-4662-ab9d-a1b14f30757b","resolution":{"observed_at":"2026-08-06T10:06:23.863919Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:25.816996Z","title":"Bangla News Article Dataset (BNAD): A Standard Repository of 1.9 Million News Articles from Nine Bangla News Websites","venue":null,"work_id":"1ed8bfd7-c1ce-4bf3-87ef-59bcd38f89a8","year":2024},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.628391Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:2ac6ae4b5d60f7686dc4e3f125b60e86e861d243076fa2141f7cd1eb128df8f5","observation_id":"0ba557a5-8233-4b1e-a233-13565b83a622","resolution":{"observed_at":"2026-08-06T10:06:25.822052Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.910124Z","title":"BanFakeNews: A Dataset for Detecting Fake News in Bangla","venue":null,"work_id":"89d9a9b0-1322-4df4-8a9e-ca4dca3cfe7d","year":2020},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.631841Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:710936a0d478ff156012e8f7285d4fa9b98d9441b17361d066b865cb9fa9bc6e","observation_id":"4f76a135-6a71-4435-9202-ede3bdeee0d8","resolution":{"observed_at":"2026-08-06T10:06:26.913470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:23.635122Z","title":"GloVe: Global Vectors for Word Representation","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.635122Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:ad763b173a693cdd3efed13a81077998ce1de948fffa9a919cfb65777f746bf1","observation_id":"b84b5cb0-7691-41b8-94c8-39e723193a8b","resolution":{"observed_at":"2026-08-06T10:06:23.635122Z","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":"2026-08-06T10:06:26.899781Z","title":"Semi-Supervised Classification with Graph Convolutional Networks","venue":null,"work_id":"624cef88-17a7-4020-a4d6-65df16717d01","year":2017},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.638442Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:df0c0994bcdef3c90b95cc68201f9c4e28bce7bb050b84e6e0ebc07c7d8930f3","observation_id":"4cc83fb1-1e3f-465c-8c2a-9babf8ed9a37","resolution":{"observed_at":"2026-08-06T10:06:26.903321Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:23.641581Z","title":"Indexing by latent semantic analysis","venue":null,"work_id":null,"year":1990},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.641581Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:230de7674a1c4345a7d11c2308f928eb258d81683a67aaa223700368795a3045","observation_id":"635ab079-a2b0-4729-9ab9-a8d540b64102","resolution":{"observed_at":"2026-08-06T10:06:23.641581Z","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":"2026-08-06T10:06:26.890350Z","title":"Neuralvariationalinferenceandlearninginbeliefnetworks","venue":null,"work_id":"4731d9b0-4f82-4cbd-bc5f-d302ebe56b23","year":2014},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.644926Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:606a1e9ea1d7ad5671ed56b04019fbf18de0968c8313c548593dd1b5904bb944","observation_id":"0c508f08-668d-4cdc-9466-32ab26145492","resolution":{"observed_at":"2026-08-06T10:06:26.893413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.880937Z","title":"Auto-encoding variational bayes","venue":null,"work_id":"cabd12ed-debf-4071-aa3e-5c381b34a651","year":2013},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.648483Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:d3f58263747e9e5b1ba47465e7a329c1ff75630b393d689008c0e2888aa6aada","observation_id":"63dc61e9-9bac-45cb-9f9b-1e3eb0b1be14","resolution":{"observed_at":"2026-08-06T10:06:26.883967Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.871554Z","title":"CluWords: exploiting semantic word clustering representation for enhanced topic modeling","venue":null,"work_id":"17aa1522-35ac-4ffe-a8cb-a2767f81b4f2","year":2019},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.652239Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:9d5100899de91496200e9449224056a5631157b6d194c83598e2c33e2f3882bb","observation_id":"15841cb3-8a5c-449d-abb9-0407ddbf261b","resolution":{"observed_at":"2026-08-06T10:06:26.874728Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.16248","last_updated":"2024-03-26T17:46:26Z","snapshot_observed_at":"2026-07-06T17:49:48.720293Z","submitted_at":"2024-03-24T17:39:51Z","title":"Large Language Models Offer an Alternative to the Traditional Approach of Topic Modelling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.16248","snapshot_observed_at":"2026-08-06T10:06:23.655340Z","title":"Large language models offer an alternative to the traditional approach of topic modelling","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.655340Z"},"links":{"cited_paper":"/paper/2403.16248","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:d0872ad379f3d8ca123e925c3ada24a36256866374e5b70c0708b8f634557b6d","observation_id":"44a02d49-ebab-4af1-9a4b-6f297898b859","resolution":{"observed_at":"2026-08-06T10:06:23.655340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.00611","last_updated":"2024-05-01T16:32:07Z","snapshot_observed_at":"2026-07-06T18:08:17.557905Z","submitted_at":"2024-05-01T16:32:07Z","title":"Addressing Topic Granularity and Hallucination in Large Language Models for Topic Modelling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.00611","snapshot_observed_at":"2026-08-06T10:06:23.659079Z","title":"Addressing topic granularity and hallucination in large language models for topic modelling","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.659079Z"},"links":{"cited_paper":"/paper/2405.00611","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:cacfd39994cdd35bf18b40079c254f615f1862e60db18651b78d8cbc8896a4be","observation_id":"aa5be899-57cd-4e43-8d9b-b25da2b19236","resolution":{"observed_at":"2026-08-06T10:06:23.659079Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.02019","last_updated":"2016-05-06T18:13:18Z","snapshot_observed_at":"2026-07-06T04:55:23.322394Z","submitted_at":"2016-05-06T18:13:18Z","title":"Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vec","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.02019","snapshot_observed_at":"2026-08-06T10:06:23.662502Z","title":"Mixing dirichlet topic models and word embeddings to make lda2vec","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.662502Z"},"links":{"cited_paper":"/paper/1605.02019","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:4be288e8512845203c4122eaa21fca0588c6bb9fad73fc5887a1bcef593baac6","observation_id":"b9da88f4-90a0-4ea3-815e-546efc72d0f8","resolution":{"observed_at":"2026-08-06T10:06:23.662502Z","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":"publication/3499734","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:25.615851Z","title":"A Systematic Literature Review on English and Bangla Topic Modeling","venue":null,"work_id":"1355a715-deb7-4e57-81d5-db68c374cf71","year":2021},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.666191Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:7f28636d0f64c460aad069f48d4bc65c99267c117a3e06ecda0a2382139af811","observation_id":"6c11821d-4253-4262-addb-0189d1244561","resolution":{"observed_at":"2026-08-06T10:06:25.620890Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:25.472418Z","title":"Bangla-BERT: Transformer- Based Efficient Model for Transfer Learning and Language Understanding","venue":null,"work_id":"e3ed566d-51ee-4569-b0d6-dd18424e6a1d","year":2022},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.669280Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:744f48286585a6e6f353f6ada2b4ea4c087c6933b34664550b3bc1de4dd90c52","observation_id":"10f40fdb-2cfa-4780-b91f-45f8fd40b113","resolution":{"observed_at":"2026-08-06T10:06:25.476053Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:25.287694Z","title":"Support vector machines and Word2vec for text classification with semantic features","venue":null,"work_id":"bec23d97-f135-4ac5-8e25-78b40c88574a","year":2015},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.672576Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:ae206a3187515d8779b7e7162490b7a1bc4f17bc1411ab7dc46cc776f2d0fcec","observation_id":"9a035190-5373-405a-b067-a738a11faa34","resolution":{"observed_at":"2026-08-06T10:06:25.291157Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:25.111856Z","title":"Measuring document similarity with weighted averages of word embeddings","venue":null,"work_id":"40bdb6b2-6014-41ca-b3d8-796655a75311","year":2023},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.676267Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:6f2431e0485246fae9221e7c4d687f28154d9877effc0571cce1a0568fe09d8c","observation_id":"19b3c792-07f0-47a8-8c59-c3e6ed6b9db0","resolution":{"observed_at":"2026-08-06T10:06:25.115966Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.09875","last_updated":"2019-02-26T11:55:35Z","snapshot_observed_at":"2026-07-06T07:35:29.946706Z","submitted_at":"2019-02-26T11:55:35Z","title":"Improving a tf-idf weighted document vector embedding","version":1},"cited_work":{"arxiv_id":"1902.09875","doi":null,"metadata_source":"pith","pith_arxiv_id":"1902.09875","snapshot_observed_at":"2026-08-06T10:06:24.962656Z","title":"Improving a tf-idf weighted document vector embedding","venue":"cs.CL","work_id":"027e1941-eaba-446d-8d71-0516befdcbb1","year":2019},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.680202Z"},"links":{"cited_paper":"/paper/1902.09875","citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:0c92d622336440045e6d06f9027e7a197daf414478d8b450b92d8488d35d7044","observation_id":"c8ad5383-b869-408d-b509-2bc40dbfe0e6","resolution":{"observed_at":"2026-08-06T10:06:24.966374Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.861811Z","title":"Graph Convolutional Networks for Text Classification","venue":null,"work_id":"a36b8b80-3e00-44c2-a12c-383140afdd9e","year":2019},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.683607Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:4d2a43972beb8419383f23a72dd5ecab694a6c59b1a747e5428643b9143d06f9","observation_id":"c0d2ade5-037c-46c1-87b1-fc0c9c5c1fe5","resolution":{"observed_at":"2026-08-06T10:06:26.865202Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.852301Z","title":"Graph Neural Networks: A Review of Methods and Applications","venue":null,"work_id":"b6f1d215-a259-4d4f-bc8c-c84072b2bcf4","year":2020},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.686986Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:d131a727a57c63f0c4c7a9d0e30c0cfd2e20b56da6a7e92cb55004f2a0f21ad7","observation_id":"3f98fef0-3a49-4e1a-b4a1-ad517e34fdc5","resolution":{"observed_at":"2026-08-06T10:06:26.855653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.842949Z","title":"A Comprehensive Survey on Graph Neural Networks","venue":null,"work_id":"7ae8da10-45fe-4c80-a6ac-b0765d8dd5fd","year":2021},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.690047Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:c966432cea5e44f888379c5512bf13fbdb1f60c87fbee4f8dc7d63b40726094f","observation_id":"2cf72041-aaa3-4456-8bc6-e04e67057668","resolution":{"observed_at":"2026-08-06T10:06:26.846059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:24.949014Z","title":"Deep Graph Contrastive Representation Learning","venue":null,"work_id":"2aa0cabf-9de6-4345-bfac-586fd690e8d5","year":2022},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.693082Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:3f4309e24ea32920427b44d4f8de3e551b9e61f651a7c5ae7408ccb1e67c6d74","observation_id":"71c6d87c-bf29-435d-9146-4ad0e41adf1d","resolution":{"observed_at":"2026-08-06T10:06:24.952229Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.832815Z","title":"Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification","venue":null,"work_id":"fa43d733-9d26-4273-8f46-3c1887e3adbe","year":2020},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.696153Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:cba6cce8cf73ca740c4df1b5d6e66deb2f33e523a2f7b1fd3a230349c60927d0","observation_id":"5ccc165f-cfbf-434f-9463-541d633c499e","resolution":{"observed_at":"2026-08-06T10:06:26.836332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:26.552903Z","title":"Hybrid Margin Contrastive Loss for Graph Neural Networks","venue":null,"work_id":"413056e0-9f50-410a-a4b8-8fb9efa3be46","year":2022},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.699366Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:a8d458927cf0c5f43b1896d6c8b88e70b5ccd6b961aa22f59ee235c69981ddee","observation_id":"1f7fd3b3-3f6a-44a1-a482-6cf692ae3f17","resolution":{"observed_at":"2026-08-06T10:06:26.556863Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:24.638425Z","title":"Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks","venue":null,"work_id":"fce90f89-7e3a-4bf7-9c1e-83cae7c9af27","year":2019},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.702765Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:7ee1e8bc33bc3fe7b5096077380c5f9874f23e92fb27d570d654b8b9fbb212b0","observation_id":"89dac003-fcd0-4f49-a5dd-1a07c5b86c61","resolution":{"observed_at":"2026-08-06T10:06:24.644646Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.823468Z","title":"A Simple Framework for Contrastive Learning of Visual Representations","venue":null,"work_id":"37de908d-4b94-419a-a779-b13ca9e38c9b","year":2020},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.705720Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:490d36d192f70c951af1cb13c3fa8dce9c37e53121b5fd2033d09476a030806d","observation_id":"5fa60b1d-3c40-43a2-9c44-5e7c8ecefb01","resolution":{"observed_at":"2026-08-06T10:06:26.826555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:24.451209Z","title":"Bangla SBERT - Sentence Embedding Using Multilingual Knowledge Distillation","venue":null,"work_id":"48ebc629-3313-4641-832e-3527b0c130af","year":2024},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.709116Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:93e9568ca85c572adda9a438408273c4d575416b85a47845399e91097841f8cb","observation_id":"3dc9c3dd-dc66-4036-bd3c-bc7f6700d20d","resolution":{"observed_at":"2026-08-06T10:06:24.454750Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.814408Z","title":"Visualizing data using t-SNE","venue":null,"work_id":"21565403-e32d-4a59-8c09-4b284bc7f805","year":2008},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.712286Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:89cdbd985cf5884b11930915dda7dbe81c0e2b17d07cd423295176e5d81403b0","observation_id":"eca37dd0-9054-416f-8840-b62cf9dbaf92","resolution":{"observed_at":"2026-08-06T10:06:26.817545Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.805137Z","title":"The Psycho-Biology of Language: An Introduction to Dynamic Philology","venue":null,"work_id":"9469e557-2c16-4823-a034-e88f091f7d68","year":1935},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.715613Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:7b244cbddf23cbca98a37ccf6698aad0ea5221a78aac486e4b8bfaae24a1677b","observation_id":"55587a06-1595-4773-ad09-1a7501ab5d52","resolution":{"observed_at":"2026-08-06T10:06:26.808352Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.795488Z","title":"Lexical Diversity and Language Development","venue":null,"work_id":"741189c3-d423-46aa-94c2-93681b77caec","year":2004},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.719081Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:5940c4c39fcb8139219a804a07c76c2c81b701bd3721bb16545884dbb6154ef0","observation_id":"c2bf13f1-fc78-45d7-b10d-5b8be19f9d5b","resolution":{"observed_at":"2026-08-06T10:06:26.798889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:23.722719Z","title":"MTLD, vocd-D, and HD-D: A Validation Study of Sophisticated Approaches to Lexical Diversity Assessment","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.722719Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:6f6d40f9e6404760671a8769281ede11cd8b9bc17b0271383a56ec5a8642199b","observation_id":"35e91c83-b3f5-45a7-a8fa-00dfb587b351","resolution":{"observed_at":"2026-08-06T10:06:23.722719Z","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":"2026-08-06T10:06:23.726085Z","title":"Cutting the Gordian Knot: The Moving-Average Type–Token Ratio","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.726085Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:20c79222e4372d7642dc07159575fba502c4a7fbdf08dcbdb4ef3c7d6fb476d6","observation_id":"3810551b-21b6-44f8-bf6a-ffcfe3f3ecd8","resolution":{"observed_at":"2026-08-06T10:06:23.726085Z","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":"10.1044/2015_jslhr-l-14-0280","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:23.809523Z","title":"Psychometric Evaluation of Lexical Diversity Indices: As- sessing Length Effects","venue":null,"work_id":"7064127c-9b3d-4018-a241-1f315dfd5f80","year":2015},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.730169Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:d5f28f5e29c5cf80deb87d641dde95d202d4a2c0bad944b8c51e4e3243480b8b","observation_id":"71b9a270-e50a-485f-8599-a4cf089f8486","resolution":{"observed_at":"2026-08-06T10:06:23.815897Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.785902Z","title":"Language and Thought","venue":null,"work_id":"52f340c4-6a9a-4d4d-ad56-5908ae83fbdd","year":1964},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.733755Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:9e6642a549564a0bc2b9e93fc4c5bd8b2b544a3f83d82d46a52f3899703ac159","observation_id":"516126cc-1bd7-4c53-be6e-8dfa34e1b0be","resolution":{"observed_at":"2026-08-06T10:06:26.789656Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.775976Z","title":"An Assessment of the Range and Usefulness of Lexical Diversity Measures and the Potential of the Measure of Textual Lexical Diversity (MTLD) [Ph.D","venue":null,"work_id":"d091e7bb-af6f-4188-a205-d705753e8741","year":2005},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.737109Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:3f974d19fa592c66bca1c389da0491200f92935f9ae99df72434eeca1f4fa415","observation_id":"92aa5f48-db5c-40ac-994a-16e544ee1609","resolution":{"observed_at":"2026-08-06T10:06:26.779375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:23.740452Z","title":"Twenty Newsgroups; 1997","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.740452Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:f6bd02c4289a89bb7a82797cd34fdb5945384c636ac939672ee7cf5f8bf02085","observation_id":"67a88241-203b-4b4f-95ec-7e75715ea8fa","resolution":{"observed_at":"2026-08-06T10:06:23.740452Z","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":"2026-08-06T10:06:26.766106Z","title":"Automatic Evaluation of Topic Coherence","venue":null,"work_id":"d8cb2319-4f60-4752-bd0f-eaf2e300bc41","year":2010},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.743803Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:8fc143c8ff6bdd5f0b4bb906625c2021e8e5b2a4208cb792853b5f8f3636ce70","observation_id":"8ed7a96e-f338-4d2a-85d2-943e03e2a30c","resolution":{"observed_at":"2026-08-06T10:06:26.769351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:24.285061Z","title":"Exploring the Space of Topic Coherence Measures","venue":null,"work_id":"f67f8a98-8a5b-4ffb-b2ed-e90b863aead1","year":2015},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.746958Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:698b109ccc8755c570eb7e4f777a6e3024616e8506defacebb16470538a0b208","observation_id":"0e752821-d96c-47cb-8c02-33f6775ecda9","resolution":{"observed_at":"2026-08-06T10:06:24.288269Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T10:06:24.085591Z","title":"A Similarity Measure for Indefinite Rankings","venue":null,"work_id":"96adb92e-37e8-4218-954d-dbbf450c1c5f","year":2010},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.749983Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:f3c88b315c9d6734940ed209a9fc433830e3794dc4d49be2435b10ecaadbd6f8","observation_id":"6802c2da-c123-45aa-8af5-fe23aa024c5f","resolution":{"observed_at":"2026-08-06T10:06:24.088898Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.755751Z","title":"Software Framework for Topic Modelling with Large Corpora","venue":null,"work_id":"647f0ee3-0597-44a4-87d3-3c18eaa46b11","year":2010},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.753160Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:a5c43822dacb4e7e91e4d2cedf83b4ca7c9e3d2b056d06fdabf05436c6d40866","observation_id":"92663592-39f1-4976-b444-23995b488fc7","resolution":{"observed_at":"2026-08-06T10:06:26.759201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:26.746454Z","title":null,"venue":null,"work_id":"726fb452-020a-4d8a-a0ba-998f76eb3f3f","year":2021},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.756860Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:80d05a7333d035f9e52f08ed5b1664183463c09f6b06459bc6666e328bcd649f","observation_id":"5967b694-913f-4732-88ae-0547c4fb37d4","resolution":{"observed_at":"2026-08-06T10:06:26.749489Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T10:06:23.760037Z","title":"Convex and semi-nonnegative matrix factorizations","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.760037Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:269dfeed46c489f52bde25990bbe0c43318a0d2adafb9ded4754f6236728f132","observation_id":"1e26db07-bdae-48e8-9d83-5ddc220eb15a","resolution":{"observed_at":"2026-08-06T10:06:23.760037Z","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":"2026-08-06T10:06:26.735638Z","title":"Statistical Comparisons of Classifiers over Multiple Data Sets","venue":null,"work_id":"cba5eae2-5738-4672-bd82-2579b412ccf4","year":2006},"citing_paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T10:06:23.763542Z"},"links":{"citing_paper":"/paper/2508.00592"},"observation_digest":"sha256:3e091f102a66e129773f2c60095cbcc90ec5079c59c2d01f7ab5717d31cb960e","observation_id":"c122f9ee-cd42-42c0-a3b5-bb39cd391dd3","resolution":{"observed_at":"2026-08-06T10:06:26.740150Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.00592","last_updated":"2025-08-01T12:45:47Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-06T10:05:54.314741Z","submitted_at":"2025-08-01T12:45:47Z","title":"GeoMoE: Divide-and-Conquer Motion Field Modeling with Mixture-of-Experts for Two-View Geometry"},"reference_resolution":{"displayed":68,"state_counts":{"malformed_identifier":3,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":24,"verified_fuzzy":27},"total_outbound_references":68},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:2508.00592."}