{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/change-detection/papers/ran/1","list_of":"/task/change-detection","task":"Change Detection","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"ran","order_definition":"only papers where Syntology ran at least one harvested sample; date (newest first), ties by arXiv id","caption":"We ran code from the paper's repository; we did not run it on this task or check it against the task's benchmarks.","absence":"A paper missing from this list is not a recorded non-run: it may have no arXiv id, no harvested code, or only samples that have not run yet.","page":1,"pages_in_order":1,"rows_per_page":100,"rows":[1,47],"of":47,"counts":{"archive_papers_tagged":919,"with_a_code_link":369,"where_syntology_ran_a_sample":47,"not_listed_spam_title":0,"listed":919,"listed_where_code_ran":47,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":42,"every_run_a_failure_of_syntologys_instrument":5,"listed_with_a_run_with_no_instrument_failure":42,"listed_every_run_a_failure_of_syntologys_instrument":5,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/change-detection/papers/ran/1","prev":null,"next":null,"papers":[{"url":"/paper/emplace-self-supervised-urban-scene-change","slug":"emplace-self-supervised-urban-scene-change","title":"EMPLACE: Self-Supervised Urban Scene Change Detection","date":"2025-03-22","arxiv_id":"2503.17716","repositories_listed":1,"syntology":{"n":7,"n_ran":4,"n_constructed":4,"n_ran_checked":4,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":7,"phrase":"4 ran (of which 4 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","sample_list":"/paper/emplace-self-supervised-urban-scene-change#ran","syntology_url":"https://syntology.ai/paper/2503.17716","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.17716"}},"official":{"repos":["timalph/emplace"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/show-me-what-and-where-has-changed-question","slug":"show-me-what-and-where-has-changed-question","title":"Show Me What and Where has Changed? Question Answering and Grounding for Remote Sensing Change Detection","date":"2024-10-31","arxiv_id":"2410.23828","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":1,"n_instrument":6,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":8,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 6 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/show-me-what-and-where-has-changed-question#ran","syntology_url":"https://syntology.ai/paper/2410.23828","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.23828"}},"official":{"repos":["like413/vista"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/an-auditing-test-to-detect-behavioral-shift","slug":"an-auditing-test-to-detect-behavioral-shift","title":"An Auditing Test To Detect Behavioral Shift in Language Models","date":"2024-10-25","arxiv_id":"2410.19406","repositories_listed":1,"syntology":{"n":8,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":8,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/an-auditing-test-to-detect-behavioral-shift#ran","syntology_url":"https://syntology.ai/paper/2410.19406","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.19406"}},"official":{"repos":["richterleo/Auditing_Test_for_LMs"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/geollava-efficient-fine-tuned-vision-language","slug":"geollava-efficient-fine-tuned-vision-language","title":"GeoLLaVA: Efficient Fine-Tuned Vision-Language Models for Temporal Change Detection in Remote Sensing","date":"2024-10-25","arxiv_id":"2410.19552","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/geollava-efficient-fine-tuned-vision-language#ran","syntology_url":"https://syntology.ai/paper/2410.19552","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.19552"}},"official":{"repos":["HosamGen/GeoLLaVA"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/teochat-a-large-vision-language-assistant-for","slug":"teochat-a-large-vision-language-assistant-for","title":"TEOChat: A Large Vision-Language Assistant for Temporal Earth Observation Data","date":"2024-10-08","arxiv_id":"2410.06234","repositories_listed":1,"syntology":{"n":9,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":5,"n_honours":2,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 2 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/teochat-a-large-vision-language-assistant-for#ran","syntology_url":"https://syntology.ai/paper/2410.06234","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2410.06234"}},"official":{"repos":["ermongroup/teochat"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/changechat-an-interactive-model-for-remote","slug":"changechat-an-interactive-model-for-remote","title":"ChangeChat: An Interactive Model for Remote Sensing Change Analysis via Multimodal Instruction Tuning","date":"2024-09-13","arxiv_id":"2409.08582","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":3,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/changechat-an-interactive-model-for-remote#ran","syntology_url":"https://syntology.ai/paper/2409.08582","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2409.08582"}},"official":{"repos":["hanlinwu/changechat"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/tempoformer-a-transformer-for-temporally","slug":"tempoformer-a-transformer-for-temporally","title":"TempoFormer: A Transformer for Temporally-aware Representations in Change Detection","date":"2024-08-28","arxiv_id":"2408.15689","repositories_listed":0,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":5,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/tempoformer-a-transformer-for-temporally#ran","syntology_url":"https://syntology.ai/paper/2408.15689","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2408.15689"}},"official":null}},{"url":"/paper/fusu-a-multi-temporal-source-land-use-change","slug":"fusu-a-multi-temporal-source-land-use-change","title":"FUSU: A Multi-temporal-source Land Use Change Segmentation Dataset for Fine-grained Urban Semantic Understanding","date":"2024-05-29","arxiv_id":"2405.19055","repositories_listed":1,"syntology":{"n":7,"n_ran":5,"n_constructed":0,"n_ran_checked":2,"n_instrument":3,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 3 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/fusu-a-multi-temporal-source-land-use-change#ran","syntology_url":"https://syntology.ai/paper/2405.19055","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.19055"}},"official":{"repos":["yuanshuai0914/fusu"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/analyzing-semantic-change-through-lexical","slug":"analyzing-semantic-change-through-lexical","title":"Analyzing Semantic Change through Lexical Replacements","date":"2024-04-29","arxiv_id":"2404.18570","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/analyzing-semantic-change-through-lexical#ran","syntology_url":"https://syntology.ai/paper/2404.18570","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.18570"}},"official":{"repos":["changeiskey/asc-lr"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/changemamba-remote-sensing-change-detection","slug":"changemamba-remote-sensing-change-detection","title":"ChangeMamba: Remote Sensing Change Detection With Spatiotemporal State Space Model","date":"2024-04-04","arxiv_id":"2404.03425","repositories_listed":1,"syntology":{"n":9,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/changemamba-remote-sensing-change-detection#ran","syntology_url":"https://syntology.ai/paper/2404.03425","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.03425"}},"official":{"repos":["chenhongruixuan/mambacd"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/rs-mamba-for-large-remote-sensing-image-dense","slug":"rs-mamba-for-large-remote-sensing-image-dense","title":"RS-Mamba for Large Remote Sensing Image Dense Prediction","date":"2024-04-03","arxiv_id":"2404.02668","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/rs-mamba-for-large-remote-sensing-image-dense#ran","syntology_url":"https://syntology.ai/paper/2404.02668","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.02668"}},"official":{"repos":["walking-shadow/Official_Remote_Sensing_Mamba"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/mtp-advancing-remote-sensing-foundation-model","slug":"mtp-advancing-remote-sensing-foundation-model","title":"MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining","date":"2024-03-20","arxiv_id":"2403.13430","repositories_listed":2,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":2,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":1,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 1 violated, 1 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/mtp-advancing-remote-sensing-foundation-model#ran","syntology_url":"https://syntology.ai/paper/2403.13430","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.13430"}},"official":{"repos":["vitae-transformer/mtp"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/segment-any-change","slug":"segment-any-change","title":"Segment Any Change","date":"2024-02-02","arxiv_id":"2402.01188","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/segment-any-change#ran","syntology_url":"https://syntology.ai/paper/2402.01188","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.01188"}},"official":{"repos":["Z-Zheng/pytorch-change-models"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/good-at-captioning-bad-at-counting","slug":"good-at-captioning-bad-at-counting","title":"Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation data","date":"2024-01-31","arxiv_id":"2401.17600","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/good-at-captioning-bad-at-counting#ran","syntology_url":"https://syntology.ai/paper/2401.17600","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.17600"}},"official":{"repos":["Earth-Intelligence-Lab/vleo-bench"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/transformer-based-multimodal-change-detection","slug":"transformer-based-multimodal-change-detection","title":"Transformer-based Multimodal Change Detection with Multitask Consistency Constraints","date":"2023-10-13","arxiv_id":"2310.09276","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/transformer-based-multimodal-change-detection#ran","syntology_url":"https://syntology.ai/paper/2310.09276","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.09276"}},"official":{"repos":["qaz670756/mmcd"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/exchange-means-change-an-unsupervised-single","slug":"exchange-means-change-an-unsupervised-single","title":"Exchange means change: an unsupervised single-temporal change detection framework based on intra- and inter-image patch exchange","date":"2023-10-01","arxiv_id":"2310.00689","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":2,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/exchange-means-change-an-unsupervised-single#ran","syntology_url":"https://syntology.ai/paper/2310.00689","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.00689"}},"official":{"repos":["chenhongruixuan/i3pe"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/scalable-multi-temporal-remote-sensing-change-1","slug":"scalable-multi-temporal-remote-sensing-change-1","title":"Scalable Multi-Temporal Remote Sensing Change Data Generation via Simulating Stochastic Change Process","date":"2023-09-29","arxiv_id":"2309.17031","repositories_listed":2,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":0,"n_instrument":5,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 5 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/scalable-multi-temporal-remote-sensing-change-1#ran","syntology_url":"https://syntology.ai/paper/2309.17031","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.17031"}},"official":{"repos":["Z-Zheng/Changen"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/convolution-and-attention-mixer-for-synthetic","slug":"convolution-and-attention-mixer-for-synthetic","title":"Convolution and Attention Mixer for Synthetic Aperture Radar Image Change Detection","date":"2023-09-21","arxiv_id":"2309.12010","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/convolution-and-attention-mixer-for-synthetic#ran","syntology_url":"https://syntology.ai/paper/2309.12010","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.12010"}},"official":{"repos":["summitgao/camixer"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/adapting-segment-anything-model-for-change","slug":"adapting-segment-anything-model-for-change","title":"Adapting Segment Anything Model for Change Detection in HR Remote Sensing Images","date":"2023-09-04","arxiv_id":"2309.01429","repositories_listed":1,"syntology":{"n":15,"n_ran":14,"n_constructed":0,"n_ran_checked":12,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":15,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/adapting-segment-anything-model-for-change#ran","syntology_url":"https://syntology.ai/paper/2309.01429","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.01429"}},"official":{"repos":["ggsding/sam-cd"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/the-change-you-want-to-see-now-in-3d","slug":"the-change-you-want-to-see-now-in-3d","title":"The Change You Want to See (Now in 3D)","date":"2023-08-21","arxiv_id":"2308.10417","repositories_listed":2,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":0,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/the-change-you-want-to-see-now-in-3d#ran","syntology_url":"https://syntology.ai/paper/2308.10417","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.10417"}},"official":{"repos":["ragavsachdeva/cyws-3d"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/fast-and-attributed-change-detection-on","slug":"fast-and-attributed-change-detection-on","title":"Fast and Attributed Change Detection on Dynamic Graphs with Density of States","date":"2023-05-15","arxiv_id":"2305.08750","repositories_listed":2,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":3,"n_instrument":4,"n_unverified":0,"n_honours":3,"n_violates":0,"n_no_contract":0,"n_pointer_only":7,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/fast-and-attributed-change-detection-on#ran","syntology_url":"https://syntology.ai/paper/2305.08750","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.08750"}},"official":{"repos":["shenyanghuang/scpd"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/dino-mc-self-supervised-contrastive-learning","slug":"dino-mc-self-supervised-contrastive-learning","title":"Extending global-local view alignment for self-supervised learning with remote sensing imagery","date":"2023-03-12","arxiv_id":"2303.06670","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/dino-mc-self-supervised-contrastive-learning#ran","syntology_url":"https://syntology.ai/paper/2303.06670","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2303.06670"}},"official":{"repos":["wennyxy/dino-mc"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/gfm-building-geospatial-foundation-models-via","slug":"gfm-building-geospatial-foundation-models-via","title":"Towards Geospatial Foundation Models via Continual Pretraining","date":"2023-02-09","arxiv_id":"2302.04476","repositories_listed":2,"syntology":{"n":6,"n_ran":2,"n_constructed":1,"n_ran_checked":2,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/gfm-building-geospatial-foundation-models-via#ran","syntology_url":"https://syntology.ai/paper/2302.04476","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2302.04476"}},"official":{"repos":["mmendiet/gfm"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":4,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/trust-but-verify-cross-modality-fusion-for-hd","slug":"trust-but-verify-cross-modality-fusion-for-hd","title":"Trust, but Verify: Cross-Modality Fusion for HD Map Change Detection","date":"2022-12-14","arxiv_id":"2212.07312","repositories_listed":2,"syntology":{"n":4,"n_ran":3,"n_constructed":1,"n_ran_checked":2,"n_instrument":1,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"phrase":"3 ran (of which 1 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/trust-but-verify-cross-modality-fusion-for-hd#ran","syntology_url":"https://syntology.ai/paper/2212.07312","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.07312"}},"official":{"repos":["johnwlambert/tbv","argoai/av2-api"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/joint-spatio-temporal-modeling-for-semantic","slug":"joint-spatio-temporal-modeling-for-semantic","title":"Joint Spatio-Temporal Modeling for the Semantic Change Detection in Remote Sensing Images","date":"2022-12-10","arxiv_id":"2212.05245","repositories_listed":3,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/joint-spatio-temporal-modeling-for-semantic#ran","syntology_url":"https://syntology.ai/paper/2212.05245","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2212.05245"}},"official":{"repos":["ggsding/scannet"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"url":"/paper/a-deep-moving-camera-background-model","slug":"a-deep-moving-camera-background-model","title":"A Deep Moving-camera Background Model","date":"2022-09-16","arxiv_id":"2209.07923","repositories_listed":1,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":1,"n_instrument":7,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 7 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/a-deep-moving-camera-background-model#ran","syntology_url":"https://syntology.ai/paper/2209.07923","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.07923"}},"official":{"repos":["bgu-cs-vil/deepmcbm"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/nonparametric-and-online-change-detection-in","slug":"nonparametric-and-online-change-detection-in","title":"Nonparametric and Online Change Detection in Multivariate Datastreams using QuantTree","date":"2022-08-30","arxiv_id":"2208.14801","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/nonparametric-and-online-change-detection-in#ran","syntology_url":"https://syntology.ai/paper/2208.14801","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2208.14801"}},"official":{"repos":["diegocarrera89/quantTree"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/chexrelnet-an-anatomy-aware-model-for","slug":"chexrelnet-an-anatomy-aware-model-for","title":"CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships between Chest X-Rays","date":"2022-08-08","arxiv_id":"2208.03873","repositories_listed":1,"syntology":{"n":7,"n_ran":7,"n_constructed":0,"n_ran_checked":7,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/chexrelnet-an-anatomy-aware-model-for#ran","syntology_url":"https://syntology.ai/paper/2208.03873","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2208.03873"}},"official":{"repos":["plan-lab/chexrelnet"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/remote-sensing-change-detection-segmentation","slug":"remote-sensing-change-detection-segmentation","title":"DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection","date":"2022-06-23","arxiv_id":"2206.11892","repositories_listed":1,"syntology":{"n":13,"n_ran":11,"n_constructed":0,"n_ran_checked":9,"n_instrument":2,"n_unverified":2,"n_honours":1,"n_violates":2,"n_no_contract":6,"n_pointer_only":7,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 2 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/remote-sensing-change-detection-segmentation#ran","syntology_url":"https://syntology.ai/paper/2206.11892","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.11892"}},"official":{"repos":["wgcban/ddpm-cd"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/how-to-reduce-change-detection-to-semantic","slug":"how-to-reduce-change-detection-to-semantic","title":"How to Reduce Change Detection to Semantic Segmentation","date":"2022-06-15","arxiv_id":"2206.07557","repositories_listed":1,"syntology":{"n":10,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/how-to-reduce-change-detection-to-semantic#ran","syntology_url":"https://syntology.ai/paper/2206.07557","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.07557"}},"official":{"repos":["DoctorKey/C-3PO"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/fast-building-segmentation-from-satellite","slug":"fast-building-segmentation-from-satellite","title":"Fast building segmentation from satellite imagery and few local labels","date":"2022-06-10","arxiv_id":"2206.05377","repositories_listed":1,"syntology":{"n":13,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":11,"n_pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 0 honoured, 0 violated, 11 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/fast-building-segmentation-from-satellite#ran","syntology_url":"https://syntology.ai/paper/2206.05377","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.05377"}},"official":null}},{"url":"/paper/scalable-online-change-detection-for-high","slug":"scalable-online-change-detection-for-high","title":"Maximum Mean Discrepancy on Exponential Windows for Online Change Detection","date":"2022-05-25","arxiv_id":"2205.12706","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/scalable-online-change-detection-for-high#ran","syntology_url":"https://syntology.ai/paper/2205.12706","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.12706"}},"official":{"repos":["flopska/mmdew-change-detector"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/a-transformer-based-siamese-network-for","slug":"a-transformer-based-siamese-network-for","title":"A Transformer-Based Siamese Network for Change Detection","date":"2022-01-04","arxiv_id":"2201.01293","repositories_listed":3,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":3,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/a-transformer-based-siamese-network-for#ran","syntology_url":"https://syntology.ai/paper/2201.01293","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.01293"}},"official":{"repos":["wgcban/changeformer"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/unsupervised-change-detection-of-extreme","slug":"unsupervised-change-detection-of-extreme","title":"Unsupervised Change Detection of Extreme Events Using ML On-Board","date":"2021-11-04","arxiv_id":"2111.02995","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":7,"n_ran_checked":7,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":8,"phrase":"7 ran (of which 7 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 7 samples that ran constructed an object rather than computing a result","sample_list":"/paper/unsupervised-change-detection-of-extreme#ran","syntology_url":"https://syntology.ai/paper/2111.02995","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.02995"}},"official":{"repos":["spaceml-org/RaVAEn"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":7,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/time-masking-for-temporal-language-models","slug":"time-masking-for-temporal-language-models","title":"Time Masking for Temporal Language Models","date":"2021-10-12","arxiv_id":"2110.06366","repositories_listed":2,"syntology":{"n":12,"n_ran":12,"n_constructed":0,"n_ran_checked":10,"n_instrument":2,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":9,"n_pointer_only":0,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 0 violated, 9 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/time-masking-for-temporal-language-models#ran","syntology_url":"https://syntology.ai/paper/2110.06366","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.06366"}},"official":{"repos":["guyrosin/tempobert"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/meta-learning-on-a-sequence-of-imbalanced","slug":"meta-learning-on-a-sequence-of-imbalanced","title":"Meta Learning on a Sequence of Imbalanced Domains with Difficulty Awareness","date":"2021-09-29","arxiv_id":"2109.14120","repositories_listed":1,"syntology":{"n":11,"n_ran":10,"n_constructed":0,"n_ran_checked":9,"n_instrument":1,"n_unverified":1,"n_honours":2,"n_violates":0,"n_no_contract":7,"n_pointer_only":4,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 2 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/meta-learning-on-a-sequence-of-imbalanced#ran","syntology_url":"https://syntology.ai/paper/2109.14120","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.14120"}},"official":{"repos":["joey-wang123/imbalancemeta"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/efficient-hybrid-transformer-learning-global","slug":"efficient-hybrid-transformer-learning-global","title":"UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery","date":"2021-09-18","arxiv_id":"2109.08937","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 2 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/efficient-hybrid-transformer-learning-global#ran","syntology_url":"https://syntology.ai/paper/2109.08937","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2109.08937"}},"official":{"repos":["WangLibo1995/GeoSeg"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/single-view-geocentric-pose-in-the-wild","slug":"single-view-geocentric-pose-in-the-wild","title":"Single View Geocentric Pose in the Wild","date":"2021-05-18","arxiv_id":"2105.08229","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/single-view-geocentric-pose-in-the-wild#ran","syntology_url":"https://syntology.ai/paper/2105.08229","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2105.08229"}},"official":{"repos":["pubgeo/monocular-geocentric-pose"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/seasonal-contrast-unsupervised-pre-training","slug":"seasonal-contrast-unsupervised-pre-training","title":"Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data","date":"2021-03-30","arxiv_id":"2103.16607","repositories_listed":5,"syntology":{"n":8,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/seasonal-contrast-unsupervised-pre-training#ran","syntology_url":"https://syntology.ai/paper/2103.16607","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.16607"}},"official":{"repos":["ElementAI/seasonal-contrast"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["listed","official"]}}},{"url":"/paper/deep-active-learning-in-remote-sensing-for","slug":"deep-active-learning-in-remote-sensing-for","title":"Deep Active Learning in Remote Sensing for data efficient Change Detection","date":"2020-08-25","arxiv_id":"2008.11201","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":2,"n_no_contract":0,"n_pointer_only":3,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 2 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/deep-active-learning-in-remote-sensing-for#ran","syntology_url":"https://syntology.ai/paper/2008.11201","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.11201"}},"official":{"repos":["previtus/ChangeDetectionProject"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/building-disaster-damage-assessment-in","slug":"building-disaster-damage-assessment-in","title":"Building Disaster Damage Assessment in Satellite Imagery with Multi-Temporal Fusion","date":"2020-04-12","arxiv_id":"2004.05525","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/building-disaster-damage-assessment-in#ran","syntology_url":"https://syntology.ai/paper/2004.05525","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.05525"}},"official":{"repos":["ethanweber/xview2"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/unsupervised-change-detection-in-multi","slug":"unsupervised-change-detection-in-multi","title":"Unsupervised Change Detection in Multi-temporal VHR Images Based on Deep Kernel PCA Convolutional Mapping Network","date":"2019-12-18","arxiv_id":"1912.08628","repositories_listed":3,"syntology":{"n":12,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/unsupervised-change-detection-in-multi#ran","syntology_url":"https://syntology.ai/paper/1912.08628","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.08628"}},"official":null}},{"url":"/paper/xbd-a-dataset-for-assessing-building-damage","slug":"xbd-a-dataset-for-assessing-building-damage","title":"xBD: A Dataset for Assessing Building Damage from Satellite Imagery","date":"2019-11-21","arxiv_id":"1911.09296","repositories_listed":4,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/xbd-a-dataset-for-assessing-building-damage#ran","syntology_url":"https://syntology.ai/paper/1911.09296","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.09296"}},"official":{"repos":["DIUx-xView/xview2-baseline"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"url":"/paper/pyannoteaudio-neural-building-blocks-for","slug":"pyannoteaudio-neural-building-blocks-for","title":"pyannote.audio: neural building blocks for speaker diarization","date":"2019-11-04","arxiv_id":"1911.01255","repositories_listed":3,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/pyannoteaudio-neural-building-blocks-for#ran","syntology_url":"https://syntology.ai/paper/1911.01255","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.01255"}},"official":{"repos":["pyannote/pyannote-audio"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/shape-and-time-distortion-loss-for-training","slug":"shape-and-time-distortion-loss-for-training","title":"Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models","date":"2019-09-19","arxiv_id":"1909.09020","repositories_listed":3,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/shape-and-time-distortion-loss-for-training#ran","syntology_url":"https://syntology.ai/paper/1909.09020","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1909.09020"}},"official":{"repos":["vincent-leguen/DILATE","vincent-leguen/STDL"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["listed"]}}},{"url":"/paper/unsupervised-deep-slow-feature-analysis-for","slug":"unsupervised-deep-slow-feature-analysis-for","title":"Unsupervised Deep Slow Feature Analysis for Change Detection in Multi-Temporal Remote Sensing Images","date":"2018-12-03","arxiv_id":"1812.00645","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/unsupervised-deep-slow-feature-analysis-for#ran","syntology_url":"https://syntology.ai/paper/1812.00645","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1812.00645"}},"official":null}},{"url":"/paper/change-detection-in-graph-streams-by-learning","slug":"change-detection-in-graph-streams-by-learning","title":"Change Detection in Graph Streams by Learning Graph Embeddings on Constant-Curvature Manifolds","date":"2018-05-16","arxiv_id":"1805.06299","repositories_listed":1,"syntology":{"n":9,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/change-detection-in-graph-streams-by-learning#ran","syntology_url":"https://syntology.ai/paper/1805.06299","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1805.06299"}},"official":{"repos":["danielegrattarola/cdt-ccm-aae"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}}],"record_sha256":"b77de0107662bf82595e7577ac267acf8e0d4e9896e162e5cc2d82c54f0d52c0","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}