{"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/mamba/papers/6","list_of":"/task/mamba","task":"Mamba","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":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":6,"pages_in_order":11,"rows_per_page":100,"rows":[501,600],"of":1058,"counts":{"archive_papers_tagged":1058,"with_a_code_link":552,"where_syntology_ran_a_sample":191,"not_listed_spam_title":0,"listed":1058,"listed_where_code_ran":191,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":177,"every_run_a_failure_of_syntologys_instrument":14,"listed_with_a_run_with_no_instrument_failure":177,"listed_every_run_a_failure_of_syntologys_instrument":14,"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/mamba","prev":"/task/mamba/papers/5","next":"/task/mamba/papers/7","papers":[{"url":"/paper/state-space-models-as-foundation-models-a","slug":"state-space-models-as-foundation-models-a","title":"State Space Models as Foundation Models: A Control Theoretic Overview","date":"2024-03-25","arxiv_id":"2403.16899","repositories_listed":1,"syntology":{"n":9,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":7,"phrase":"6 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; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/state-space-models-as-foundation-models-a#ran","syntology_url":"https://syntology.ai/paper/2403.16899","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.16899"}},"official":{"repos":["jsie7/ssm-benchmark"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/uncovering-selective-state-space-model-s","slug":"uncovering-selective-state-space-model-s","title":"Uncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation","date":"2024-03-25","arxiv_id":"2403.16371","repositories_listed":1,"syntology":{"n":5,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":5,"phrase":"3 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; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/uncovering-selective-state-space-model-s#ran","syntology_url":"https://syntology.ai/paper/2403.16371","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.16371"}},"official":{"repos":["nancheng58/recmamba"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/vmrnn-integrating-vision-mamba-and-lstm-for","slug":"vmrnn-integrating-vision-mamba-and-lstm-for","title":"VMRNN: Integrating Vision Mamba and LSTM for Efficient and Accurate Spatiotemporal Forecasting","date":"2024-03-25","arxiv_id":"2403.16536","repositories_listed":1,"syntology":null},{"url":"/paper/cobra-extending-mamba-to-multi-modal-large","slug":"cobra-extending-mamba-to-multi-modal-large","title":"Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference","date":"2024-03-21","arxiv_id":"2403.14520","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/cobra-extending-mamba-to-multi-modal-large#ran","syntology_url":"https://syntology.ai/paper/2403.14520","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.14520"}},"official":{"repos":["h-zhao1997/cobra"],"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/h-vmunet-high-order-vision-mamba-unet-for","slug":"h-vmunet-high-order-vision-mamba-unet-for","title":"H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation","date":"2024-03-20","arxiv_id":"2403.13642","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":5,"n_pointer_only":6,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/h-vmunet-high-order-vision-mamba-unet-for#ran","syntology_url":"https://syntology.ai/paper/2403.13642","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.13642"}},"official":{"repos":["wurenkai/h-vmunet"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/zigma-zigzag-mamba-diffusion-model","slug":"zigma-zigzag-mamba-diffusion-model","title":"ZigMa: A DiT-style Zigzag Mamba Diffusion Model","date":"2024-03-20","arxiv_id":"2403.13802","repositories_listed":1,"syntology":{"n":14,"n_ran":13,"n_constructed":0,"n_ran_checked":10,"n_instrument":3,"n_unverified":1,"n_honours":1,"n_violates":1,"n_no_contract":8,"n_pointer_only":4,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 1 violated, 8 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/zigma-zigzag-mamba-diffusion-model#ran","syntology_url":"https://syntology.ai/paper/2403.13802","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.13802"}},"official":{"repos":["CompVis/zigma"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/stg-mamba-spatial-temporal-graph-learning-via","slug":"stg-mamba-spatial-temporal-graph-learning-via","title":"STG-Mamba: Spatial-Temporal Graph Learning via Selective State Space Model","date":"2024-03-19","arxiv_id":"2403.12418","repositories_listed":1,"syntology":{"n":5,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":5,"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) · 3 unverified","sample_list":"/paper/stg-mamba-spatial-temporal-graph-learning-via#ran","syntology_url":"https://syntology.ai/paper/2403.12418","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.12418"}},"official":{"repos":["LincanLi98/STG-Mamba"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/is-mamba-effective-for-time-series","slug":"is-mamba-effective-for-time-series","title":"Is Mamba Effective for Time Series Forecasting?","date":"2024-03-17","arxiv_id":"2403.11144","repositories_listed":1,"syntology":null},{"url":"/paper/efficientvmamba-atrous-selective-scan-for","slug":"efficientvmamba-atrous-selective-scan-for","title":"EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba","date":"2024-03-15","arxiv_id":"2403.09977","repositories_listed":1,"syntology":{"n":18,"n_ran":9,"n_constructed":0,"n_ran_checked":7,"n_instrument":2,"n_unverified":9,"n_honours":1,"n_violates":0,"n_no_contract":6,"n_pointer_only":18,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 0 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 9 unverified","sample_list":"/paper/efficientvmamba-atrous-selective-scan-for#ran","syntology_url":"https://syntology.ai/paper/2403.09977","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.09977"}},"official":{"repos":["terrypei/efficientvmamba"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":9,"ran_from_kinds":["official"]}}},{"url":"/paper/mamba-an-effective-world-model-approach-for","slug":"mamba-an-effective-world-model-approach-for","title":"MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning","date":"2024-03-14","arxiv_id":"2403.09859","repositories_listed":1,"syntology":{"n":9,"n_ran":7,"n_constructed":0,"n_ran_checked":5,"n_instrument":2,"n_unverified":2,"n_honours":2,"n_violates":0,"n_no_contract":3,"n_pointer_only":9,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 2 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/mamba-an-effective-world-model-approach-for#ran","syntology_url":"https://syntology.ai/paper/2403.09859","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.09859"}},"official":{"repos":["zoharri/mamba"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/mambatalk-efficient-holistic-gesture","slug":"mambatalk-efficient-holistic-gesture","title":"MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models","date":"2024-03-14","arxiv_id":"2403.09471","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/mambatalk-efficient-holistic-gesture#ran","syntology_url":"https://syntology.ai/paper/2403.09471","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.09471"}},"official":{"repos":["kkakkkka/MambaTalk"],"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/timemachine-a-time-series-is-worth-4-mambas","slug":"timemachine-a-time-series-is-worth-4-mambas","title":"TimeMachine: A Time Series is Worth 4 Mambas for Long-term Forecasting","date":"2024-03-14","arxiv_id":"2403.09898","repositories_listed":1,"syntology":{"n":5,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"0 ran · 5 unverified","sample_list":"/paper/timemachine-a-time-series-is-worth-4-mambas#ran","syntology_url":"https://syntology.ai/paper/2403.09898","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.09898"}},"official":{"repos":["atik-ahamed/timemachine"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":5,"ran_from_kinds":[]}}},{"url":"/paper/video-mamba-suite-state-space-model-as-a","slug":"video-mamba-suite-state-space-model-as-a","title":"Video Mamba Suite: State Space Model as a Versatile Alternative for Video Understanding","date":"2024-03-14","arxiv_id":"2403.09626","repositories_listed":1,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":2,"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) · 3 unverified","sample_list":"/paper/video-mamba-suite-state-space-model-as-a#ran","syntology_url":"https://syntology.ai/paper/2403.09626","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.09626"}},"official":{"repos":["opengvlab/video-mamba-suite"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/vm-unet-v2-rethinking-vision-mamba-unet-for","slug":"vm-unet-v2-rethinking-vision-mamba-unet-for","title":"VM-UNET-V2 Rethinking Vision Mamba UNet for Medical Image Segmentation","date":"2024-03-14","arxiv_id":"2403.09157","repositories_listed":1,"syntology":null},{"url":"/paper/activating-wider-areas-in-image-super","slug":"activating-wider-areas-in-image-super","title":"Activating Wider Areas in Image Super-Resolution","date":"2024-03-13","arxiv_id":"2403.08330","repositories_listed":1,"syntology":{"n":15,"n_ran":12,"n_constructed":0,"n_ran_checked":6,"n_instrument":6,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":8,"phrase":"12 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; 6 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/activating-wider-areas-in-image-super#ran","syntology_url":"https://syntology.ai/paper/2403.08330","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.08330"}},"official":null}},{"url":"/paper/motion-mamba-efficient-and-long-sequence","slug":"motion-mamba-efficient-and-long-sequence","title":"Motion Mamba: Efficient and Long Sequence Motion Generation","date":"2024-03-12","arxiv_id":"2403.07487","repositories_listed":1,"syntology":null},{"url":"/paper/ssm-meets-video-diffusion-models-efficient","slug":"ssm-meets-video-diffusion-models-efficient","title":"SSM Meets Video Diffusion Models: Efficient Long-Term Video Generation with Structured State Spaces","date":"2024-03-12","arxiv_id":"2403.07711","repositories_listed":1,"syntology":{"n":11,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":4,"n_no_contract":2,"n_pointer_only":2,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 4 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/ssm-meets-video-diffusion-models-efficient#ran","syntology_url":"https://syntology.ai/paper/2403.07711","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.07711"}},"official":{"repos":["shim0114/ssm-meets-video-diffusion-models"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/point-mamba-a-novel-point-cloud-backbone","slug":"point-mamba-a-novel-point-cloud-backbone","title":"Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy","date":"2024-03-11","arxiv_id":"2403.06467","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":3,"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/point-mamba-a-novel-point-cloud-backbone#ran","syntology_url":"https://syntology.ai/paper/2403.06467","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.06467"}},"official":{"repos":["irmvlab/point-mamba"],"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/the-pitfalls-of-next-token-prediction","slug":"the-pitfalls-of-next-token-prediction","title":"The pitfalls of next-token prediction","date":"2024-03-11","arxiv_id":"2403.06963","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":7,"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) · 1 unverified","sample_list":"/paper/the-pitfalls-of-next-token-prediction#ran","syntology_url":"https://syntology.ai/paper/2403.06963","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.06963"}},"official":{"repos":["gregorbachmann/next-token-failures"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/clinicalmamba-a-generative-clinical-language","slug":"clinicalmamba-a-generative-clinical-language","title":"ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes","date":"2024-03-09","arxiv_id":"2403.05795","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":1,"n_no_contract":6,"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, 1 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/clinicalmamba-a-generative-clinical-language#ran","syntology_url":"https://syntology.ai/paper/2403.05795","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.05795"}},"official":{"repos":["whaleloops/clinicalmamba"],"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/lightm-unet-mamba-assists-in-lightweight-unet","slug":"lightm-unet-mamba-assists-in-lightweight-unet","title":"LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation","date":"2024-03-08","arxiv_id":"2403.05246","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":2,"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) · 0 unverified","sample_list":"/paper/lightm-unet-mamba-assists-in-lightweight-unet#ran","syntology_url":"https://syntology.ai/paper/2403.05246","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.05246"}},"official":{"repos":["mrblankness/lightm-unet"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/mammil-multiple-instance-learning-for-whole","slug":"mammil-multiple-instance-learning-for-whole","title":"MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models","date":"2024-03-08","arxiv_id":"2403.05160","repositories_listed":1,"syntology":null},{"url":"/paper/motion-guided-dual-camera-tracker-for-low","slug":"motion-guided-dual-camera-tracker-for-low","title":"Motion-Guided Dual-Camera Tracker for Endoscope Tracking and Motion Analysis in a Mechanical Gastric Simulator","date":"2024-03-08","arxiv_id":"2403.05146","repositories_listed":1,"syntology":null},{"url":"/paper/medmamba-vision-mamba-for-medical-image","slug":"medmamba-vision-mamba-for-medical-image","title":"MedMamba: Vision Mamba for Medical Image Classification","date":"2024-03-06","arxiv_id":"2403.03849","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/medmamba-vision-mamba-for-medical-image#ran","syntology_url":"https://syntology.ai/paper/2403.03849","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.03849"}},"official":{"repos":["YubiaoYue/MedMamba"],"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/mim-istd-mamba-in-mamba-for-efficient","slug":"mim-istd-mamba-in-mamba-for-efficient","title":"MiM-ISTD: Mamba-in-Mamba for Efficient Infrared Small Target Detection","date":"2024-03-04","arxiv_id":"2403.02148","repositories_listed":1,"syntology":null},{"url":"/paper/the-hidden-attention-of-mamba-models","slug":"the-hidden-attention-of-mamba-models","title":"The Hidden Attention of Mamba Models","date":"2024-03-03","arxiv_id":"2403.01590","repositories_listed":1,"syntology":{"n":8,"n_ran":6,"n_constructed":0,"n_ran_checked":5,"n_instrument":1,"n_unverified":2,"n_honours":1,"n_violates":0,"n_no_contract":4,"n_pointer_only":8,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/the-hidden-attention-of-mamba-models#ran","syntology_url":"https://syntology.ai/paper/2403.01590","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.01590"}},"official":{"repos":["ameenali/hiddenmambaattn"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/theoretical-foundations-of-deep-selective","slug":"theoretical-foundations-of-deep-selective","title":"Theoretical Foundations of Deep Selective State-Space Models","date":"2024-02-29","arxiv_id":"2402.19047","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/theoretical-foundations-of-deep-selective#ran","syntology_url":"https://syntology.ai/paper/2402.19047","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.19047"}},"official":{"repos":["benjamin-walker/selective-ssms-and-linear-cdes"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/evaluating-quantized-large-language-models","slug":"evaluating-quantized-large-language-models","title":"Evaluating Quantized Large Language Models","date":"2024-02-28","arxiv_id":"2402.18158","repositories_listed":1,"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":3,"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/evaluating-quantized-large-language-models#ran","syntology_url":"https://syntology.ai/paper/2402.18158","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.18158"}},"official":{"repos":["thu-nics/qllm-eval"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/log-neural-controlled-differential-equations","slug":"log-neural-controlled-differential-equations","title":"Log Neural Controlled Differential Equations: The Lie Brackets Make a Difference","date":"2024-02-28","arxiv_id":"2402.18512","repositories_listed":1,"syntology":null},{"url":"/paper/densemamba-state-space-models-with-dense","slug":"densemamba-state-space-models-with-dense","title":"DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models","date":"2024-02-26","arxiv_id":"2403.00818","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/densemamba-state-space-models-with-dense#ran","syntology_url":"https://syntology.ai/paper/2403.00818","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2403.00818"}},"official":{"repos":["wailordhe/densessm"],"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/res-vmamba-fine-grained-food-category-visual","slug":"res-vmamba-fine-grained-food-category-visual","title":"Res-VMamba: Fine-Grained Food Category Visual Classification Using Selective State Space Models with Deep Residual Learning","date":"2024-02-24","arxiv_id":"2402.15761","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":3,"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; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/res-vmamba-fine-grained-food-category-visual#ran","syntology_url":"https://syntology.ai/paper/2402.15761","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.15761"}},"official":{"repos":["chishengchen/resvmamba"],"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/pan-mamba-effective-pan-sharpening-with-state","slug":"pan-mamba-effective-pan-sharpening-with-state","title":"Pan-Mamba: Effective pan-sharpening with State Space Model","date":"2024-02-19","arxiv_id":"2402.12192","repositories_listed":1,"syntology":{"n":13,"n_ran":12,"n_constructed":0,"n_ran_checked":6,"n_instrument":6,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":5,"n_pointer_only":13,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 1 violated, 5 with no contract checked; 6 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/pan-mamba-effective-pan-sharpening-with-state#ran","syntology_url":"https://syntology.ai/paper/2402.12192","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.12192"}},"official":{"repos":["alexhe101/pan-mamba"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/pointmamba-a-simple-state-space-model-for","slug":"pointmamba-a-simple-state-space-model-for","title":"PointMamba: A Simple State Space Model for Point Cloud Analysis","date":"2024-02-16","arxiv_id":"2402.10739","repositories_listed":1,"syntology":{"n":11,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":7,"n_pointer_only":5,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/pointmamba-a-simple-state-space-model-for#ran","syntology_url":"https://syntology.ai/paper/2402.10739","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.10739"}},"official":{"repos":["lmd0311/pointmamba"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/hierarchical-state-space-models-for","slug":"hierarchical-state-space-models-for","title":"Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling","date":"2024-02-15","arxiv_id":"2402.10211","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/hierarchical-state-space-models-for#ran","syntology_url":"https://syntology.ai/paper/2402.10211","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.10211"}},"official":{"repos":["raunaqbhirangi/hiss"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/graph-mamba-towards-learning-on-graphs-with","slug":"graph-mamba-towards-learning-on-graphs-with","title":"Graph Mamba: Towards Learning on Graphs with State Space Models","date":"2024-02-13","arxiv_id":"2402.08678","repositories_listed":1,"syntology":null},{"url":"/paper/semi-mamba-unet-pixel-level-contrastive-cross","slug":"semi-mamba-unet-pixel-level-contrastive-cross","title":"Semi-Mamba-UNet: Pixel-Level Contrastive and Pixel-Level Cross-Supervised Visual Mamba-based UNet for Semi-Supervised Medical Image Segmentation","date":"2024-02-11","arxiv_id":"2402.07245","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":0,"n_honours":1,"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; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/semi-mamba-unet-pixel-level-contrastive-cross#ran","syntology_url":"https://syntology.ai/paper/2402.07245","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.07245"}},"official":{"repos":["ziyangwang007/mamba-unet"],"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":["official"]}}},{"url":"/paper/mamba-nd-selective-state-space-modeling-for","slug":"mamba-nd-selective-state-space-modeling-for","title":"Mamba-ND: Selective State Space Modeling for Multi-Dimensional Data","date":"2024-02-08","arxiv_id":"2402.05892","repositories_listed":1,"syntology":{"n":11,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":11,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/mamba-nd-selective-state-space-modeling-for#ran","syntology_url":"https://syntology.ai/paper/2402.05892","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.05892"}},"official":{"repos":["jacklishufan/mamba-nd"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/mamba-unet-unet-like-pure-visual-mamba-for","slug":"mamba-unet-unet-like-pure-visual-mamba-for","title":"Mamba-UNet: UNet-Like Pure Visual Mamba for Medical Image Segmentation","date":"2024-02-07","arxiv_id":"2402.05079","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":0,"n_honours":3,"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; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/mamba-unet-unet-like-pure-visual-mamba-for#ran","syntology_url":"https://syntology.ai/paper/2402.05079","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.05079"}},"official":{"repos":["ziyangwang007/mamba-unet"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/u-shaped-vision-mamba-for-single-image","slug":"u-shaped-vision-mamba-for-single-image","title":"U-shaped Vision Mamba for Single Image Dehazing","date":"2024-02-06","arxiv_id":"2402.04139","repositories_listed":1,"syntology":null},{"url":"/paper/is-mamba-capable-of-in-context-learning","slug":"is-mamba-capable-of-in-context-learning","title":"Is Mamba Capable of In-Context Learning?","date":"2024-02-05","arxiv_id":"2402.03170","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":6,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":8,"phrase":"7 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; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/is-mamba-capable-of-in-context-learning#ran","syntology_url":"https://syntology.ai/paper/2402.03170","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.03170"}},"official":{"repos":["automl/is_mamba_capable_of_icl"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/nnmamba-3d-biomedical-image-segmentation","slug":"nnmamba-3d-biomedical-image-segmentation","title":"nnMamba: 3D Biomedical Image Segmentation, Classification and Landmark Detection with State Space Model","date":"2024-02-05","arxiv_id":"2402.03526","repositories_listed":1,"syntology":null},{"url":"/paper/swin-umamba-mamba-based-unet-with-imagenet","slug":"swin-umamba-mamba-based-unet-with-imagenet","title":"Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining","date":"2024-02-05","arxiv_id":"2402.03302","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":2,"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) · 0 unverified","sample_list":"/paper/swin-umamba-mamba-based-unet-with-imagenet#ran","syntology_url":"https://syntology.ai/paper/2402.03302","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.03302"}},"official":{"repos":["jiarunliu/swin-umamba"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/blackmamba-mixture-of-experts-for-state-space","slug":"blackmamba-mixture-of-experts-for-state-space","title":"BlackMamba: Mixture of Experts for State-Space Models","date":"2024-02-01","arxiv_id":"2402.01771","repositories_listed":1,"syntology":null},{"url":"/paper/graph-mamba-towards-long-range-graph-sequence","slug":"graph-mamba-towards-long-range-graph-sequence","title":"Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces","date":"2024-02-01","arxiv_id":"2402.00789","repositories_listed":1,"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/graph-mamba-towards-long-range-graph-sequence#ran","syntology_url":"https://syntology.ai/paper/2402.00789","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2402.00789"}},"official":null}},{"url":"/paper/vivim-a-video-vision-mamba-for-medical-video","slug":"vivim-a-video-vision-mamba-for-medical-video","title":"Vivim: a Video Vision Mamba for Medical Video Segmentation","date":"2024-01-25","arxiv_id":"2401.14168","repositories_listed":1,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":6,"n_instrument":4,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":13,"phrase":"10 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; 4 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/vivim-a-video-vision-mamba-for-medical-video#ran","syntology_url":"https://syntology.ai/paper/2401.14168","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.14168"}},"official":{"repos":["scott-yjyang/vivim"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/segmamba-long-range-sequential-modeling-mamba","slug":"segmamba-long-range-sequential-modeling-mamba","title":"SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation","date":"2024-01-24","arxiv_id":"2401.13560","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":1,"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: 1 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/segmamba-long-range-sequential-modeling-mamba#ran","syntology_url":"https://syntology.ai/paper/2401.13560","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.13560"}},"official":{"repos":["ge-xing/segmamba"],"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/mamba-multi-level-aggregation-via-memory-bank","slug":"mamba-multi-level-aggregation-via-memory-bank","title":"MAMBA: Multi-level Aggregation via Memory Bank for Video Object Detection","date":"2024-01-18","arxiv_id":"2401.09923","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/mamba-multi-level-aggregation-via-memory-bank#ran","syntology_url":"https://syntology.ai/paper/2401.09923","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.09923"}},"official":{"repos":["guanxiongsun/vfe.pytorch"],"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/mambatab-a-simple-yet-effective-approach-for","slug":"mambatab-a-simple-yet-effective-approach-for","title":"MambaTab: A Plug-and-Play Model for Learning Tabular Data","date":"2024-01-16","arxiv_id":"2401.08867","repositories_listed":1,"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":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) · 2 unverified","sample_list":"/paper/mambatab-a-simple-yet-effective-approach-for#ran","syntology_url":"https://syntology.ai/paper/2401.08867","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.08867"}},"official":{"repos":["atik-ahamed/mambatab"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/u-mamba-enhancing-long-range-dependency-for","slug":"u-mamba-enhancing-long-range-dependency-for","title":"U-Mamba: Enhancing Long-range Dependency for Biomedical Image Segmentation","date":"2024-01-09","arxiv_id":"2401.04722","repositories_listed":1,"syntology":null},{"url":"/paper/moe-mamba-efficient-selective-state-space","slug":"moe-mamba-efficient-selective-state-space","title":"MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts","date":"2024-01-08","arxiv_id":"2401.04081","repositories_listed":1,"syntology":null},{"url":"/paper/weakly-supervised-ai-for-efficient-analysis","slug":"weakly-supervised-ai-for-efficient-analysis","title":"Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples","date":"2023-07-27","arxiv_id":"2307.14907","repositories_listed":1,"syntology":null},{"url":"/paper/scalable-multi-agent-model-based","slug":"scalable-multi-agent-model-based","title":"Scalable Multi-Agent Model-Based Reinforcement Learning","date":"2022-05-25","arxiv_id":"2205.15023","repositories_listed":1,"syntology":null},{"url":null,"slug":"a-real-time-system-for-egocentric-hand-object","title":"A Real-Time System for Egocentric Hand-Object Interaction Detection in Industrial Domains","date":"2025-07-17","arxiv_id":"2507.13326","repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-medical-image-segmentation-with-state","title":"Unified Medical Image Segmentation with State Space Modeling Snake","date":"2025-07-17","arxiv_id":"2507.12760","repositories_listed":0,"syntology":null},{"url":null,"slug":"adaptive-gate-aware-mamba-networks-for","title":"Adaptive Gate-Aware Mamba Networks for Magnetic Resonance Fingerprinting","date":"2025-07-04","arxiv_id":"2507.03369","repositories_listed":0,"syntology":null},{"url":null,"slug":"strumamba3d-exploring-structural-mamba-for","title":"StruMamba3D: Exploring Structural Mamba for Self-supervised Point Cloud Representation Learning","date":"2025-06-26","arxiv_id":"2506.21541","repositories_listed":0,"syntology":null},{"url":null,"slug":"eagle-an-efficient-global-attention-lesion","title":"EAGLE: An Efficient Global Attention Lesion Segmentation Model for Hepatic Echinococcosis","date":"2025-06-25","arxiv_id":"2506.20333","repositories_listed":0,"syntology":null},{"url":null,"slug":"flightkooba-a-fast-interpretable-ftp-model","title":"FlightKooba: A Fast Interpretable FTP Model","date":"2025-06-24","arxiv_id":"2506.19885","repositories_listed":0,"syntology":null},{"url":null,"slug":"jcapt-a-joint-modeling-approach-for-capt","title":"JCAPT: A Joint Modeling Approach for CAPT","date":"2025-06-24","arxiv_id":"2506.19315","repositories_listed":0,"syntology":null},{"url":null,"slug":"memba-membrane-driven-parameter-efficient","title":"Memba: Membrane-driven Parameter-Efficient Fine-Tuning for Mamba","date":"2025-06-22","arxiv_id":"2506.18184","repositories_listed":0,"syntology":null},{"url":null,"slug":"state-space-models-in-efficient-whispered-and","title":"State-Space Models in Efficient Whispered and Multi-dialect Speech Recognition","date":"2025-06-20","arxiv_id":"2506.16969","repositories_listed":0,"syntology":null},{"url":null,"slug":"ednet-a-distortion-agnostic-speech","title":"EDNet: A Distortion-Agnostic Speech Enhancement Framework with Gating Mamba Mechanism and Phase Shift-Invariant Training","date":"2025-06-19","arxiv_id":"2506.16231","repositories_listed":0,"syntology":null},{"url":null,"slug":"flowram-grounding-flow-matching-policy-with-1","title":"FlowRAM: Grounding Flow Matching Policy with Region-Aware Mamba Framework for Robotic Manipulation","date":"2025-06-19","arxiv_id":"2506.16201","repositories_listed":0,"syntology":null},{"url":null,"slug":"fadpnet-frequency-aware-dual-path-network-for","title":"FADPNet: Frequency-Aware Dual-Path Network for Face Super-Resolution","date":"2025-06-17","arxiv_id":"2506.14121","repositories_listed":0,"syntology":null},{"url":null,"slug":"mt-pcr-a-hybrid-mamba-transformer-with","title":"MT-PCR: A Hybrid Mamba-Transformer with Spatial Serialization for Hierarchical Point Cloud Registration","date":"2025-06-16","arxiv_id":"2506.13183","repositories_listed":0,"syntology":null},{"url":null,"slug":"scaling-algorithm-distillation-for-continuous","title":"Scaling Algorithm Distillation for Continuous Control with Mamba","date":"2025-06-16","arxiv_id":"2506.13892","repositories_listed":0,"syntology":null},{"url":null,"slug":"stereo-sound-event-localization-and-detection","title":"Stereo sound event localization and detection based on PSELDnet pretraining and BiMamba sequence modeling","date":"2025-06-16","arxiv_id":"2506.13455","repositories_listed":0,"syntology":null},{"url":null,"slug":"m4v-multi-modal-mamba-for-text-to-video","title":"M4V: Multi-Modal Mamba for Text-to-Video Generation","date":"2025-06-12","arxiv_id":"2506.10915","repositories_listed":0,"syntology":null},{"url":null,"slug":"sequential-parallel-duality-in-prefix","title":"Sequential-Parallel Duality in Prefix Scannable Models","date":"2025-06-12","arxiv_id":"2506.10918","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparsessm-efficient-selective-structured","title":"SparseSSM: Efficient Selective Structured State Space Models Can Be Pruned in One-Shot","date":"2025-06-11","arxiv_id":"2506.09613","repositories_listed":0,"syntology":null},{"url":null,"slug":"ecmnet-lightweight-semantic-segmentation-with","title":"ECMNet:Lightweight Semantic Segmentation with Efficient CNN-Mamba Network","date":"2025-06-10","arxiv_id":"2506.08629","repositories_listed":0,"syntology":null},{"url":null,"slug":"mlvtg-mamba-based-feature-alignment-and-llm","title":"MLVTG: Mamba-Based Feature Alignment and LLM-Driven Purification for Multi-Modal Video Temporal Grounding","date":"2025-06-10","arxiv_id":"2506.08512","repositories_listed":0,"syntology":null},{"url":"/paper/sema-a-scalable-and-efficient-mamba-like","slug":"sema-a-scalable-and-efficient-mamba-like","title":"SEMA: a Scalable and Efficient Mamba like Attention via Token Localization and Averaging","date":"2025-06-10","arxiv_id":"2506.08297","repositories_listed":0,"syntology":{"n":13,"n_ran":10,"n_constructed":0,"n_ran_checked":10,"n_instrument":0,"n_unverified":3,"n_honours":1,"n_violates":2,"n_no_contract":7,"n_pointer_only":13,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 1 honoured, 2 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/sema-a-scalable-and-efficient-mamba-like#ran","syntology_url":"https://syntology.ai/paper/2506.08297","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2506.08297"}},"official":null}},{"url":null,"slug":"fmamil-frequency-driven-mamba-multi-instance","title":"FMaMIL: Frequency-Driven Mamba Multi-Instance Learning for Weakly Supervised Lesion Segmentation in Medical Images","date":"2025-06-09","arxiv_id":"2506.07652","repositories_listed":0,"syntology":null},{"url":null,"slug":"m2restore-mixture-of-experts-based-mamba-cnn","title":"M2Restore: Mixture-of-Experts-based Mamba-CNN Fusion Framework for All-in-One Image Restoration","date":"2025-06-09","arxiv_id":"2506.07814","repositories_listed":0,"syntology":null},{"url":null,"slug":"2506-05297","title":"DM-SegNet: Dual-Mamba Architecture for 3D Medical Image Segmentation with Global Context Modeling","date":"2025-06-05","arxiv_id":"2506.05297","repositories_listed":0,"syntology":null},{"url":null,"slug":"log-linear-attention","title":"Log-Linear Attention","date":"2025-06-05","arxiv_id":"2506.04761","repositories_listed":0,"syntology":null},{"url":null,"slug":"mambanext-yolo-a-hybrid-state-space-model-for","title":"MambaNeXt-YOLO: A Hybrid State Space Model for Real-time Object Detection","date":"2025-06-04","arxiv_id":"2506.03654","repositories_listed":0,"syntology":null},{"url":null,"slug":"comba-improving-bilinear-rnns-with-closed","title":"Comba: Improving Bilinear RNNs with Closed-loop Control","date":"2025-06-03","arxiv_id":"2506.02475","repositories_listed":0,"syntology":null},{"url":null,"slug":"are-mamba-based-audio-foundation-models-the","title":"Are Mamba-based Audio Foundation Models the Best Fit for Non-Verbal Emotion Recognition?","date":"2025-06-02","arxiv_id":"2506.02258","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-skeleton-based-action-recognition-a-review","title":"3D Skeleton-Based Action Recognition: A Review","date":"2025-06-01","arxiv_id":"2506.00915","repositories_listed":0,"syntology":null},{"url":null,"slug":"general-purpose-audio-representation-learning","title":"General-purpose audio representation learning for real-world sound scenes","date":"2025-06-01","arxiv_id":"2506.00934","repositories_listed":0,"syntology":null},{"url":null,"slug":"mamba-drafters-for-speculative-decoding","title":"Mamba Drafters for Speculative Decoding","date":"2025-06-01","arxiv_id":"2506.01206","repositories_listed":0,"syntology":null},{"url":null,"slug":"parrot-synergizing-mamba-and-attention-based","title":"PARROT: Synergizing Mamba and Attention-based SSL Pre-Trained Models via Parallel Branch Hadamard Optimal Transport for Speech Emotion Recognition","date":"2025-06-01","arxiv_id":"2506.01138","repositories_listed":0,"syntology":null},{"url":null,"slug":"acm-unet-adaptive-integration-of-cnns-and","title":"ACM-UNet: Adaptive Integration of CNNs and Mamba for Efficient Medical Image Segmentation","date":"2025-05-30","arxiv_id":"2505.24481","repositories_listed":0,"syntology":null},{"url":null,"slug":"mamba-integrated-with-physics-principles","title":"Mamba Integrated with Physics Principles Masters Long-term Chaotic System Forecasting","date":"2025-05-29","arxiv_id":"2505.23863","repositories_listed":0,"syntology":null},{"url":"/paper/rivermamba-a-state-space-model-for-global","slug":"rivermamba-a-state-space-model-for-global","title":"RiverMamba: A State Space Model for Global River Discharge and Flood Forecasting","date":"2025-05-28","arxiv_id":"2505.22535","repositories_listed":0,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/rivermamba-a-state-space-model-for-global#ran","syntology_url":"https://syntology.ai/paper/2505.22535","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2505.22535"}},"official":null}},{"url":null,"slug":"statespacediffuser-bringing-long-context-to","title":"StateSpaceDiffuser: Bringing Long Context to Diffusion World Models","date":"2025-05-28","arxiv_id":"2505.22246","repositories_listed":0,"syntology":null},{"url":null,"slug":"htmnet-a-hybrid-network-with-transformer","title":"HTMNet: A Hybrid Network with Transformer-Mamba Bottleneck Multimodal Fusion for Transparent and Reflective Objects Depth Completion","date":"2025-05-27","arxiv_id":"2505.20904","repositories_listed":0,"syntology":null},{"url":null,"slug":"occle-label-efficient-3d-semantic-occupancy","title":"OccLE: Label-Efficient 3D Semantic Occupancy Prediction","date":"2025-05-27","arxiv_id":"2505.20617","repositories_listed":0,"syntology":null},{"url":null,"slug":"scaling-up-liquid-resistance-liquid","title":"Scaling Up Liquid-Resistance Liquid-Capacitance Networks for Efficient Sequence Modeling","date":"2025-05-27","arxiv_id":"2505.21717","repositories_listed":0,"syntology":null},{"url":null,"slug":"zigzagpointmamba-spatial-semantic-mamba-for","title":"ZigzagPointMamba: Spatial-Semantic Mamba for Point Cloud Understanding","date":"2025-05-27","arxiv_id":"2505.21381","repositories_listed":0,"syntology":null},{"url":null,"slug":"fastmamba-a-high-speed-and-efficient-mamba","title":"FastMamba: A High-Speed and Efficient Mamba Accelerator on FPGA with Accurate Quantization","date":"2025-05-25","arxiv_id":"2505.18975","repositories_listed":0,"syntology":null},{"url":null,"slug":"latent-mamba-operator-for-partial","title":"Latent Mamba Operator for Partial Differential Equations","date":"2025-05-25","arxiv_id":"2505.19105","repositories_listed":0,"syntology":null},{"url":null,"slug":"evm-fusion-an-explainable-vision-mamba","title":"EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion","date":"2025-05-23","arxiv_id":"2505.17367","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-mamba-transformer-decoder-for-error","title":"Hybrid Mamba-Transformer Decoder for Error-Correcting Codes","date":"2025-05-23","arxiv_id":"2505.17834","repositories_listed":0,"syntology":null},{"url":null,"slug":"selection-mechanisms-for-sequence-modeling","title":"Selection Mechanisms for Sequence Modeling using Linear State Space Models","date":"2025-05-23","arxiv_id":"2505.17932","repositories_listed":0,"syntology":null},{"url":null,"slug":"weakly-supervised-mamba-based-mastoidectomy","title":"Weakly-supervised Mamba-Based Mastoidectomy Shape Prediction for Cochlear Implant Surgery Using 3D T-Distribution Loss","date":"2025-05-23","arxiv_id":"2505.18368","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-speech-enhancement-active-speech","title":"Active Speech Enhancement: Active Speech Denoising Decliping and Deveraberation","date":"2025-05-22","arxiv_id":"2505.16911","repositories_listed":0,"syntology":null},{"url":null,"slug":"pcmamba-physics-informed-cross-modal-state","title":"PCMamba: Physics-Informed Cross-Modal State Space Model for Dual-Camera Compressive Hyperspectral Imaging","date":"2025-05-22","arxiv_id":"2505.16373","repositories_listed":0,"syntology":null}],"record_sha256":"d6304c4781c83d163d610c506d48d2499b1edf314c4b4f8cddc69f40a13db808","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}