{"as_of":"2026-08-05T03:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6604192f5dca1725c0b4dee5e7a342ba90bbb71a0d892bafe560d40f56b9cbca","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T20:08:16.828717Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+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/2606.07725/citation-record","integrity":"/paper/2606.07725/integrity","json":"/paper/2606.07725/citation-record.json","paper":"/paper/2606.07725"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T20:08:16.828717Z","title":"Geodynamics,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:15e00b545ac199a42d0a5dd9c401b663dc8bc46f4e0b7a573d2c0419560bac9d","observation_id":"8a24f390-c1b8-493c-bc5c-a696a1e7d748","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Harnessing the GPS data explosion for interdisciplinary science,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:041f99652e544173d859acc08e9d72a0df7b65d6383ea54ae3d022d19628abf3","observation_id":"20993f48-590c-4f52-911e-a84901452b3e","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Discontinuity detection in GNSS station coordinate time series using machine learning,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:79419d54200e1783ea6eab077ea7381a291527a0eb0c9f801e11a07d8c22fdbb","observation_id":"39d8f7d2-83a0-4ee6-ba14-e4607a5690bd","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"An improved VMD-LSTM model for time-varying GNSS time series prediction with temporally correlated noise,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:c9b1c164549c20a6ea3bcd185a8e7ebe4c202245b44138b46f268840b3aefa7b","observation_id":"3dafeb1a-8f82-496d-8c76-97fad0477a7e","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Multi-station deep learning on geodetic time series detects slow slip events in cascadia,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:61ff9f65055fd550b354c903a0c1aceba4a1fc9b0308cc821fba9803729c906a","observation_id":"d0ed542c-d27f-45fc-8d70-fd662d2e1eb8","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"BERT: Pre- training of deep bidirectional transformers for language understanding,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:ce2322f4e9d50fa80425417ca1b6d2f5b423a668b37abf106e41720ba874f7e7","observation_id":"01f62d51-ad2d-4dfd-94ae-5b2d8c3c7dac","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Masked autoencoders are scalable vision learners,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:7c1b604f100761f9e060e006f2140b3cf998939db66814a3d699e7a38c470044","observation_id":"68c828e8-20da-4afb-9377-760279e7eff5","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2111.06377","last_updated":"2021-12-19T19:23:25Z","snapshot_observed_at":"2026-07-31T02:35:46.853381Z","submitted_at":"2021-11-11T18:46:40Z","title":"Masked Autoencoders Are Scalable Vision Learners","version":3},"cited_work":{"arxiv_id":"2111.06377","doi":"10.48550/arxiv.2111.06377","metadata_source":"pith","pith_arxiv_id":"2111.06377","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Masked Autoencoders Are Scalable Vision Learners","venue":"cs.CV","work_id":"0747476e-5bd0-4596-908f-391611d9364e","year":2021},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"cited_paper":"/paper/2111.06377","citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:eb587a394c3339876c01be1c8eaad9b7de418b195d828ea916f7f77d26895b6c","observation_id":"4fa1420c-78c3-4262-aece-be89f7c28652","resolution":{"observed_at":"2026-07-02T20:47:23.115626Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-07-11T01:49:44.938872+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T01:49:44.938872+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-27T20:08:16.828717Z","title":"wav2vec 2.0: A framework for self-supervised learning of speech representations,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:08b103b0c7716878fc1b0c8af6ac0e61fc8bec4d2a4275089a5e86ea277c7f5d","observation_id":"a74b19e7-f9cd-4897-bcb7-922ba8cb520b","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.15765","last_updated":"2024-10-21T08:24:44Z","snapshot_observed_at":"2026-07-06T19:36:54.626904Z","submitted_at":"2024-10-21T08:24:44Z","title":"SeisLM: a Foundation Model for Seismic Waveforms","version":1},"cited_work":{"arxiv_id":"2410.15765","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.15765","snapshot_observed_at":"2026-07-02T20:47:23.121247Z","title":"SeisLM: a foundation model for seismic waveforms,","venue":null,"work_id":"ed44380f-29ca-4b72-8c3d-735bd10ab4a2","year":2024},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"cited_paper":"/paper/2410.15765","citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:cafb171aafe71ae7b5276fe722b94806c3202685190e96f83d0c738f9eed9105","observation_id":"41f0dfc0-a4df-4d3d-9469-52e3faf05d9b","resolution":{"observed_at":"2026-07-02T20:47:23.122731Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-27T20:08:16.828717Z","title":"Beit: Bert pre-training of image transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:c0b836e36703e4318866e473f6d2265072dabee8fbae0b38e5895b88690deeeb","observation_id":"902ad608-b961-4e27-8c40-eec87183ee3c","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Feature guided masked autoencoder for self-supervised learning in remote sens- ing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:a5010e11515cc97b1bcd7338460a879e4a60fd3ddd85046fb7faa96df32cadb9","observation_id":"deb3d705-342c-4ccd-8392-34f599e6b765","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"HuBERT: Self-supervised speech representation learning by masked prediction of hidden units,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:13d4462df4244bc6c5e5d365b5293c3937b7fa3618f2d853125ce978ba503cf0","observation_id":"5c6910e4-bc2a-4fcc-a13a-c7de1adf797f","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"WavLM: Large-scale self-supervised pre-training for full stack speech processing,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:af0de02af33024c29a6bbd5709f59229ca1b3b577d263db4e385061b9216a5e3","observation_id":"1fe5bdf0-71a2-43bc-b673-093cbc9bc0eb","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"TS2Vec: Towards universal representation of time series,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:ce884c382502007b3acab84ce3275d013b16ad314106fa14641b9901540a534e","observation_id":"d994a704-e5c3-43a6-a610-b6844fd3858f","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"A transformer-based framework for multivariate time series representation learning,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:2d638937148cde61039f5345c165daa1da2faa7b2d2c852fa8e5b427ac3159a3","observation_id":"e16ef245-a619-49bb-a408-5036d9d92e3e","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Vector quantization pretraining for EEG time series with random projection and phase alignment,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:75e4b65d5e5cbf9866a8d538ce65a8dac4d8b1cae766bc3ffe737bd86917ffec","observation_id":"99e23c8a-6bc3-4095-a440-9e48ea9b1be5","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Effective self-supervised transformers for sparse time series data,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:ba31bb32151bd7216d58252c99dab003dd19499b4fb25c73566c939f6a03ada6","observation_id":"59b0615e-55e0-4cea-a8ef-7a1628358ab2","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Self-supervised spatio-temporal representation learning of satellite image time series,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:4ee63c89fcc488509d22c7da37138d35436b92bae47de2e0ed02782af918820e","observation_id":"0981015e-7033-4b74-8912-cabd06b53e7d","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.07815","last_updated":"2024-11-04T17:42:45Z","snapshot_observed_at":"2026-07-06T17:43:27.034067Z","submitted_at":"2024-03-12T16:53:54Z","title":"Chronos: Learning the Language of Time Series","version":3},"cited_work":{"arxiv_id":"2403.07815","doi":"10.48550/arxiv.2403.07815","metadata_source":"pith","pith_arxiv_id":"2403.07815","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Chronos: Learning the Language of Time Series","venue":"cs.LG","work_id":"d8b9a3a4-4dd9-4544-8c39-96b0be0b7af0","year":2024},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"cited_paper":"/paper/2403.07815","citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:a0ce544e2aaeeafab9b2e74d231393e3324459a3fb4f1a9568af147eee0602ca","observation_id":"26cafcd8-6a27-4f91-916c-cfe84b58be3a","resolution":{"observed_at":"2026-07-02T20:47:23.113062Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-07-12T09:20:17.505608+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T09:20:17.505608+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10688","last_updated":"2024-04-17T18:24:45Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-14T17:01:37Z","title":"A decoder-only foundation model for time-series forecasting","version":4},"cited_work":{"arxiv_id":"2310.10688","doi":"10.48550/arxiv.2310.10688","metadata_source":"pith","pith_arxiv_id":"2310.10688","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A decoder-only foundation model for time-series forecasting","venue":"cs.CL","work_id":"a4d7bd2f-9620-47d6-8c8f-0f25283a9f57","year":2023},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"cited_paper":"/paper/2310.10688","citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:6630240cc8236666be7af5e249c1b5846b60a420749cf5c1a6433f089ed07f61","observation_id":"1c6c710c-7dcf-432e-ac70-76884994d26b","resolution":{"observed_at":"2026-07-02T20:47:23.123181Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-07-12T22:51:01.59061+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T22:51:01.59061+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.03589","last_updated":"2024-05-27T23:34:15Z","snapshot_observed_at":"2026-07-06T16:28:18.257251Z","submitted_at":"2023-10-05T15:14:00Z","title":"TimeGPT-1","version":3},"cited_work":{"arxiv_id":"2310.03589","doi":"10.48550/arxiv.2310.03589","metadata_source":"pith","pith_arxiv_id":"2310.03589","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Timegpt-1","venue":"cs.LG","work_id":"af6502b8-ba1d-4b47-a197-a64760f6bf14","year":2023},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"cited_paper":"/paper/2310.03589","citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:47290904f4e4aa7c0311878b51fb31191c302c95063eda6fc87bd469b6eddf2f","observation_id":"e9507ac3-ba9b-4c00-ad28-bfcdf9813204","resolution":{"observed_at":"2026-07-02T20:47:23.114904Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-27T20:08:16.828717Z","title":"A foundation model for the earth system,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:8d8784e28164c3712449643d9b3d9f4e3ea14471d2d5548d04e0474a6fb2e0f5","observation_id":"970cb9cb-b2df-43f2-8b75-16f9ab9b6243","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Integrating GNSS- derived atmospheric delays into large weather foundation models,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:f008988f8cef0e807aa49e9eb8b8ac5255392f98c7bdf7c6b5787e528eed3e6f","observation_id":"ea0cd1e3-f317-438a-a12d-cb8a8e3dc028","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Earth system foundation model (esfm): A unified framework for heterogeneous data integration and forecasting,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:41b30fb55232daa028d6066eb49b5ae0efc5c116294da27283db91b82f522eb8","observation_id":"35f385cd-32c0-4ace-8afd-6e80b2e37b6f","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Alphaearth foundations: An embedding field model for accurate and efficient global mapping from sparse label data,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:ff937b983b34436aebd57a9d1671b398e228560325d62a2daab938c12ebe4fc4","observation_id":"65b977aa-0d90-4bd2-8866-fae1dfd274fb","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Denoising daily displacement GNSS time series using deep neural networks in a near real-time framing: a single-station method,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:a842d82205b08b4ff9a8b59f0e560af9b7bd5d24081f6e86dfb473d85d66f592","observation_id":"8eed8730-8979-4018-bd16-0887473f4066","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Cascadia daily GNSS time series denoising: Graph neural network and stack filtering,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:6c667d6fefae78d9993f3ee9b44bf6522c117d4e552880e616e053b4735e4c55","observation_id":"61b63d39-bcc3-436b-8f72-c3c36c645701","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Modeling of residual GNSS station motions through meteorological data in a machine learning approach,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:44d9be2952a602c5990ecdb09a79bca361fac4f15dff0ee9eb0312091647ea39","observation_id":"7ca3a266-8208-42ad-bd4c-f1899790121d","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Correction models for GNSS displacements in europe based on en- vironmental variables and XGBoost,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:ae6a49f766b29d8b7db7e35061aead7afd53ace19be39fb1253210679cad7fd0","observation_id":"6d3ce037-4435-4ed2-ae39-ef5e98e2510a","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Modelling of GNSS station position time series using deep learning approaches,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:268864de4f180a130acc103c38c03a8ad80bfae003d196682055507937a2f892","observation_id":"755bfef9-bedc-4b8b-bee9-7a71c27ae350","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Kiani Shahvandi and B","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:9e9ba68aceb402d9666e0f14c7649931727512c5d4ccaaf71d556aac806886f8","observation_id":"9ce765fd-56e4-426f-9fb4-421624b1dd9a","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"The effect of coloured noise on the uncertainties of rates estimated from geodetic time series,","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:faea194f724b66a85d66d174ab696da653481a13dda7290f7672e47a12144410","observation_id":"cbd19192-7ebe-4018-97f5-3554b2a9b534","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Anatomy of apparent seasonal variations from GPS-derived site position time series,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:2f7c8ecfd4014de4ef07ccc5e4741dedfaf3696f0200042e99b43407d2df74a3","observation_id":"15d5a09c-a3ba-43f6-a623-c66d05b8c8b8","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Itrf2020: an augmented reference frame refining the modeling of nonlinear station motions,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:494220e88e4947f2c5a6f61fdd46c238caa3f1dd5a95d3e183c84ce2e6921e10","observation_id":"ff757268-2417-4828-9d2b-f491b70e2387","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Wdowinski, Y","venue":null,"work_id":null,"year":1992},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:3975667ee264c52094208088d30638963a401e91cb38d0dbe556b6d3fa65d8f0","observation_id":"de3848b9-eff2-45ae-95a3-bfd80300a875","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Spa- tiotemporal filtering using principal component analysis and karhunen– lo`eve expansion approaches to GPS coordinate time series,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:b586648167e3c2b60279825a59444664b1d53dbd0d7ead410f6b721884147619","observation_id":"4abb52dd-5359-4ae4-a16c-1088d57a7360","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Noise-resilient GNSS coordinate time series prediction using A VMD-sLSTM-transformer hybrid model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:13e4b534792b71fa1d6c071b4541b4a73664403d17d05576069d4b458a63bf8c","observation_id":"6cfd4f2c-e2ce-4ff1-a765-8189a88d89ed","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Generalized hampel filters,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:6eed73bb9e0661877e71dfe0a0f9c4ad31ebbc2e7c603e374de6381b0fe2f9f3","observation_id":"8b2243c7-1ec7-4d2a-aacf-b9b0e61fe655","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"The identification of multiple outliers,","venue":null,"work_id":null,"year":1993},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:bf05fb16b63a1aa8a2b39dc7bae04bbc8257a8fa542d8e621f2600967954c0cb","observation_id":"40c0367b-e277-4bd7-b438-a6f9c6728ae3","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"The jackknife and the bootstrap for general stationary observations,","venue":null,"work_id":null,"year":1989},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:9e4d96a1c520f61075993cb4d48937bd16919752a59843db83107725c2332e53","observation_id":"d1e2406e-c266-486d-a044-e6a243398c33","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"A nearest neighbor bootstrap for resampling hydrologic time series,","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:ca683e3e48bd5313f004328e06952b22832363743958e097f269892c4fbdc4e6","observation_id":"18d7e6f0-ad5e-4903-b276-a85c74bb9e48","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"End-to-end object detection with transformers,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:a8885c6f700381492f899b30487c3a508edcc8eba61284057aec18596a013b1c","observation_id":"4f7eb32d-0250-4988-96ef-ae09470f090e","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1607.06450","last_updated":"2016-07-21T19:57:52Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2016-07-21T19:57:52Z","title":"Layer Normalization","version":1},"cited_work":{"arxiv_id":"1607.06450","doi":"10.1007/978-3-319-32025-0","metadata_source":"pith","pith_arxiv_id":"1607.06450","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Layer Normalization","venue":"stat.ML","work_id":"20a2d720-0046-4c7c-bcd6-327ec8143f69","year":2016},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"cited_paper":"/paper/1607.06450","citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:fbbf085852495e6278147a01d3edbc1b312c541da81c680d5a994568510631e4","observation_id":"a17f4077-6887-4b06-8319-f31a8f118b30","resolution":{"observed_at":"2026-07-02T20:47:23.126000Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.08415","last_updated":"2023-06-06T01:53:32Z","snapshot_observed_at":"2026-07-06T05:01:27.910364Z","submitted_at":"2016-06-27T19:20:40Z","title":"Gaussian Error Linear Units (GELUs)","version":5},"cited_work":{"arxiv_id":"1606.08415","doi":"10.18653/v1/n19-1122","metadata_source":"pith","pith_arxiv_id":"1606.08415","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Gaussian Error Linear Units (GELUs)","venue":"cs.LG","work_id":"0466fd22-03a1-4a61-af0a-a900e77bb023","year":2016},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"cited_paper":"/paper/1606.08415","citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:51f34b7f1fcbc473831ebded0cf3d81795f92aa85df77fcb1f0f27e790879d6f","observation_id":"53cdaf93-67ed-4ed6-bfae-2ef3d25aa348","resolution":{"observed_at":"2026-07-02T20:47:23.128870Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-27T20:08:16.828717Z","title":"Go- ing deeper with image transformers,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:d20dc0dfcbda213197466179ed6388668ab8ef9c6e4e721f9b452d9528a8b93f","observation_id":"15f1d4bf-9b86-48a1-a65b-344d988e3008","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"FiLM: Visual reasoning with a general conditioning layer,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:06bb50671c23064646cbe74a76cfa6fb00880b152c045dc0ceea02a6ab504896","observation_id":"f8dcd8f2-cd57-4429-b0bc-c61f589e4c10","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Categorical reparameterization with Gumbel-Softmax,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:1c68b57b7bc0daf3dda1fa65f1bc729ef47d9f8b55473f0785d238201364cac9","observation_id":"dcd04e32-5e47-4e1b-b01b-193c904bbab0","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Representation learning with contrastive predictive coding,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:fc8fcf5f3427e271b2075b7075e341177aade071d0a8eb5315d2bb6ae37f4067","observation_id":"11c198c0-b0fc-4541-a1ae-10772653bae9","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":"2106.09685","doi":"10.4088/pcc.v03n0609","metadata_source":"pith","pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","venue":"cs.CL","work_id":"0426219a-789e-4964-adc8-a04538510818","year":2021},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:6e24c27cc513f2098cc659a1ac3051a24cebc2c0c4bb01b99c2cb56b0d8de3d3","observation_id":"63dcc019-a518-4bcd-9cdc-da217387d811","resolution":{"observed_at":"2026-07-02T20:47:23.107007Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.14730","last_updated":"2023-03-05T22:11:56Z","snapshot_observed_at":"2026-07-31T22:45:35.561492Z","submitted_at":"2022-11-27T05:15:42Z","title":"A Time Series is Worth 64 Words: Long-term Forecasting with Transformers","version":2},"cited_work":{"arxiv_id":"2211.14730","doi":"10.48550/arxiv.2211.14730","metadata_source":"pith","pith_arxiv_id":"2211.14730","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Time Series is Worth 64 Words: Long-term Forecasting with Transformers","venue":"cs.LG","work_id":"d6d0a3ac-d695-4de0-ba2d-4e1d31ac8359","year":2022},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"cited_paper":"/paper/2211.14730","citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:da1fb8060b2046499486857d4ea64a8744a1e78413600d8e5974c73335494416","observation_id":"0bca7e45-c1c3-4290-9634-a37954bd3988","resolution":{"observed_at":"2026-07-02T20:47:23.120859Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-07-12T09:20:18.545813+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T09:20:18.545813+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-27T20:08:16.828717Z","title":"DAB-DETR: Dynamic anchor boxes are better queries for DETR,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:60bbd2b28fab3744f1a041712e7ce7dd71b8decb3b33c94a31d6cc66d3004a76","observation_id":"c1c415dd-80cb-4ee8-9e6e-b38862088bb0","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"Mallat,A Wavelet Tour of Signal Processing: The Sparse Way, 3rd ed","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:ba636f7c94740ced696c69da61a25e2117ed726ef13d98fb5d00076089e77d10","observation_id":"be6aab9d-888b-4551-8cbf-d9f5d3f4f6fe","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"XGBoost: A scalable tree boosting system,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:a0c8d97850f1bb2640026751e7f1ce8f3cc2e7f60320fa8217480a7dc88830c0","observation_id":"293c958f-9936-4bf1-9208-218d87c07fb6","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","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":"2026-06-27T20:08:16.828717Z","title":"On a test of whether one of two random variables is stochastically larger than the other,","venue":null,"work_id":null,"year":1947},"citing_paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-06-27T20:08:16.828717Z"},"links":{"citing_paper":"/paper/2606.07725"},"observation_digest":"sha256:23208f3f54305dc62ea0a835a4d6fd7ffd9ec860a9b1c7c2332535565e08ae2b","observation_id":"5d78aa5e-c119-40af-87fa-4653c0addeeb","resolution":{"observed_at":"2026-06-27T20:08:16.828717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.07725","last_updated":"2026-06-05T16:39:49Z","latest_version":1,"primary_category":"physics.geo-ph","snapshot_observed_at":"2026-08-02T15:30:06.087972Z","submitted_at":"2026-06-05T16:39:49Z","title":"GNSS-FM: A Self-Supervised Foundation Model for Daily GNSS Displacement Time Series"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":46,"verified_exact":8,"verified_fuzzy":0},"total_outbound_references":55},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2606.07725."}