{"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/attribute/papers/10","list_of":"/task/attribute","task":"Attribute","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":10,"pages_in_order":54,"rows_per_page":100,"rows":[901,1000],"of":5387,"counts":{"archive_papers_tagged":5387,"with_a_code_link":1923,"where_syntology_ran_a_sample":475,"not_listed_spam_title":0,"listed":5387,"listed_where_code_ran":475,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":387,"every_run_a_failure_of_syntologys_instrument":88,"listed_with_a_run_with_no_instrument_failure":387,"listed_every_run_a_failure_of_syntologys_instrument":88,"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/attribute","prev":"/task/attribute/papers/9","next":"/task/attribute/papers/11","papers":[{"url":"/paper/syn-att-synthetic-speech-attribution-via-semi","slug":"syn-att-synthetic-speech-attribution-via-semi","title":"Syn-Att: Synthetic Speech Attribution via Semi-Supervised Unknown Multi-Class Ensemble of CNNs","date":"2023-09-15","arxiv_id":"2309.08146","repositories_listed":1,"syntology":null},{"url":"/paper/towards-large-scale-building-attribute","slug":"towards-large-scale-building-attribute","title":"Towards Large-scale Building Attribute Mapping using Crowdsourced Images: Scene Text Recognition on Flickr and Problems to be Solved","date":"2023-09-14","arxiv_id":"2309.08042","repositories_listed":1,"syntology":null},{"url":"/paper/a-sequentially-fair-mechanism-for-multiple","slug":"a-sequentially-fair-mechanism-for-multiple","title":"A Sequentially Fair Mechanism for Multiple Sensitive Attributes","date":"2023-09-12","arxiv_id":"2309.06627","repositories_listed":1,"syntology":null},{"url":"/paper/narrowing-the-gap-between-supervised-and","slug":"narrowing-the-gap-between-supervised-and","title":"Narrowing the Gap between Supervised and Unsupervised Sentence Representation Learning with Large Language Model","date":"2023-09-12","arxiv_id":"2309.06453","repositories_listed":1,"syntology":null},{"url":"/paper/2309-05804","slug":"2309-05804","title":"Hi Model, generating 'nice' instead of 'good' is not as bad as generating 'rice'! Towards Context and Semantic Infused Dialogue Generation Loss Function and Evaluation Metric","date":"2023-09-11","arxiv_id":"2309.05804","repositories_listed":1,"syntology":null},{"url":"/paper/iti-gen-inclusive-text-to-image-generation","slug":"iti-gen-inclusive-text-to-image-generation","title":"ITI-GEN: Inclusive Text-to-Image Generation","date":"2023-09-11","arxiv_id":"2309.05569","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":4,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":3,"n_pointer_only":5,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 1 violated, 3 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/iti-gen-inclusive-text-to-image-generation#ran","syntology_url":"https://syntology.ai/paper/2309.05569","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.05569"}},"official":{"repos":["humansensinglab/ITI-GEN"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/unikg-a-benchmark-and-universal-embedding-for","slug":"unikg-a-benchmark-and-universal-embedding-for","title":"UniKG: A Benchmark and Universal Embedding for Large-Scale Knowledge Graphs","date":"2023-09-11","arxiv_id":"2309.05269","repositories_listed":1,"syntology":null},{"url":"/paper/redundancy-free-self-supervised-relational","slug":"redundancy-free-self-supervised-relational","title":"Redundancy-Free Self-Supervised Relational Learning for Graph Clustering","date":"2023-09-09","arxiv_id":"2309.04694","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/redundancy-free-self-supervised-relational#ran","syntology_url":"https://syntology.ai/paper/2309.04694","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.04694"}},"official":{"repos":["yisiyu95/r2fgc"],"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/motif-aware-attribute-masking-for-molecular","slug":"motif-aware-attribute-masking-for-molecular","title":"Motif-aware Attribute Masking for Molecular Graph Pre-training","date":"2023-09-08","arxiv_id":"2309.04589","repositories_listed":1,"syntology":{"n":10,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":4,"n_honours":1,"n_violates":0,"n_no_contract":5,"n_pointer_only":10,"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) · 4 unverified","sample_list":"/paper/motif-aware-attribute-masking-for-molecular#ran","syntology_url":"https://syntology.ai/paper/2309.04589","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.04589"}},"official":{"repos":["einae-nd/moama-dev"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/open-vocabulary-semantic-segmentation-via","slug":"open-vocabulary-semantic-segmentation-via","title":"AttrSeg: Open-Vocabulary Semantic Segmentation via Attribute Decomposition-Aggregation","date":"2023-08-31","arxiv_id":"2309.00096","repositories_listed":1,"syntology":null},{"url":"/paper/corrembed-evaluating-pre-trained-model-image","slug":"corrembed-evaluating-pre-trained-model-image","title":"CorrEmbed: Evaluating Pre-trained Model Image Similarity Efficacy with a Novel Metric","date":"2023-08-30","arxiv_id":"2308.16126","repositories_listed":1,"syntology":null},{"url":"/paper/substrate-geometry-affects-population","slug":"substrate-geometry-affects-population","title":"Substrate geometry affects population dynamics in a bacterial biofilm","date":"2023-08-30","arxiv_id":"2308.16046","repositories_listed":1,"syntology":null},{"url":"/paper/zero-shot-inversion-process-for-image","slug":"zero-shot-inversion-process-for-image","title":"Textual and Visual Prompt Fusion for Image Editing via Step-Wise Alignment","date":"2023-08-30","arxiv_id":"2308.15854","repositories_listed":1,"syntology":null},{"url":"/paper/facechain-a-playground-for-identity","slug":"facechain-a-playground-for-identity","title":"FaceChain: A Playground for Human-centric Artificial Intelligence Generated Content","date":"2023-08-28","arxiv_id":"2308.14256","repositories_listed":1,"syntology":null},{"url":"/paper/unpaired-multi-domain-attribute-translation","slug":"unpaired-multi-domain-attribute-translation","title":"Unpaired Multi-domain Attribute Translation of 3D Facial Shapes with a Square and Symmetric Geometric Map","date":"2023-08-25","arxiv_id":"2308.13245","repositories_listed":1,"syntology":null},{"url":"/paper/can-linguistic-knowledge-improve-multimodal","slug":"can-linguistic-knowledge-improve-multimodal","title":"Can Linguistic Knowledge Improve Multimodal Alignment in Vision-Language Pretraining?","date":"2023-08-24","arxiv_id":"2308.12898","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/can-linguistic-knowledge-improve-multimodal#ran","syntology_url":"https://syntology.ai/paper/2308.12898","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.12898"}},"official":{"repos":["wangfei-2019/snare"],"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":["official"]}}},{"url":"/paper/citetracker-correlating-image-and-text-for","slug":"citetracker-correlating-image-and-text-for","title":"CiteTracker: Correlating Image and Text for Visual Tracking","date":"2023-08-22","arxiv_id":"2308.11322","repositories_listed":1,"syntology":{"n":11,"n_ran":11,"n_constructed":0,"n_ran_checked":11,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":10,"n_pointer_only":11,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 1 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/citetracker-correlating-image-and-text-for#ran","syntology_url":"https://syntology.ai/paper/2308.11322","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.11322"}},"official":{"repos":["norahgreen/citetracker"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/m3ps-end-to-end-multi-grained-multi-modal","slug":"m3ps-end-to-end-multi-grained-multi-modal","title":"MMAPS: End-to-End Multi-Grained Multi-Modal Attribute-Aware Product Summarization","date":"2023-08-22","arxiv_id":"2308.11351","repositories_listed":1,"syntology":null},{"url":"/paper/swinface-a-multi-task-transformer-for-face","slug":"swinface-a-multi-task-transformer-for-face","title":"SwinFace: A Multi-task Transformer for Face Recognition, Expression Recognition, Age Estimation and Attribute Estimation","date":"2023-08-22","arxiv_id":"2308.11509","repositories_listed":1,"syntology":null},{"url":"/paper/villa-fine-grained-vision-language","slug":"villa-fine-grained-vision-language","title":"ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data","date":"2023-08-22","arxiv_id":"2308.11194","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 1 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) · 3 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/villa-fine-grained-vision-language#ran","syntology_url":"https://syntology.ai/paper/2308.11194","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.11194"}},"official":{"repos":["stanfordmimi/villa"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/dpan-dynamic-preference-based-and-attribute","slug":"dpan-dynamic-preference-based-and-attribute","title":"DPAN: Dynamic Preference-based and Attribute-aware Network for Relevant Recommendations","date":"2023-08-21","arxiv_id":"2308.10527","repositories_listed":1,"syntology":null},{"url":"/paper/exploring-fine-grained-representation-and","slug":"exploring-fine-grained-representation-and","title":"Exploring Fine-Grained Representation and Recomposition for Cloth-Changing Person Re-Identification","date":"2023-08-21","arxiv_id":"2308.10692","repositories_listed":1,"syntology":null},{"url":"/paper/ted-spad-temporal-distinctiveness-for-self","slug":"ted-spad-temporal-distinctiveness-for-self","title":"TeD-SPAD: Temporal Distinctiveness for Self-supervised Privacy-preservation for video Anomaly Detection","date":"2023-08-21","arxiv_id":"2308.11072","repositories_listed":1,"syntology":{"n":7,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":1,"n_no_contract":2,"n_pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 1 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/ted-spad-temporal-distinctiveness-for-self#ran","syntology_url":"https://syntology.ai/paper/2308.11072","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.11072"}},"official":{"repos":["ucf-crcv/ted-spad"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/geodtr-toward-generic-cross-view","slug":"geodtr-toward-generic-cross-view","title":"GeoDTR+: Toward generic cross-view geolocalization via geometric disentanglement","date":"2023-08-18","arxiv_id":"2308.09624","repositories_listed":1,"syntology":null},{"url":"/paper/gigamae-generalizable-graph-masked","slug":"gigamae-generalizable-graph-masked","title":"GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction","date":"2023-08-18","arxiv_id":"2308.09663","repositories_listed":1,"syntology":{"n":10,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":10,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/gigamae-generalizable-graph-masked#ran","syntology_url":"https://syntology.ai/paper/2308.09663","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.09663"}},"official":{"repos":["sycny/gigamae"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/independent-distribution-regularization-for","slug":"independent-distribution-regularization-for","title":"Independent Distribution Regularization for Private Graph Embedding","date":"2023-08-16","arxiv_id":"2308.08360","repositories_listed":1,"syntology":null},{"url":"/paper/knowledge-enhanced-multi-label-few-shot","slug":"knowledge-enhanced-multi-label-few-shot","title":"Knowledge-Enhanced Multi-Label Few-Shot Product Attribute-Value Extraction","date":"2023-08-16","arxiv_id":"2308.08413","repositories_listed":1,"syntology":null},{"url":"/paper/boosting-multi-modal-model-performance-with","slug":"boosting-multi-modal-model-performance-with","title":"Boosting Multi-modal Model Performance with Adaptive Gradient Modulation","date":"2023-08-15","arxiv_id":"2308.07686","repositories_listed":1,"syntology":{"n":15,"n_ran":10,"n_constructed":0,"n_ran_checked":7,"n_instrument":3,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":7,"n_pointer_only":1,"phrase":"10 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; 3 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/boosting-multi-modal-model-performance-with#ran","syntology_url":"https://syntology.ai/paper/2308.07686","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.07686"}},"official":{"repos":["lihong2303/agm_iccv2023"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/hierarchical-visual-primitive-experts-for","slug":"hierarchical-visual-primitive-experts-for","title":"Hierarchical Visual Primitive Experts for Compositional Zero-Shot Learning","date":"2023-08-08","arxiv_id":"2308.04016","repositories_listed":1,"syntology":{"n":12,"n_ran":11,"n_constructed":0,"n_ran_checked":8,"n_instrument":3,"n_unverified":1,"n_honours":1,"n_violates":0,"n_no_contract":7,"n_pointer_only":12,"phrase":"11 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; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/hierarchical-visual-primitive-experts-for#ran","syntology_url":"https://syntology.ai/paper/2308.04016","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.04016"}},"official":{"repos":["hanjaekim98/cot"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/unsupervised-camouflaged-object-segmentation","slug":"unsupervised-camouflaged-object-segmentation","title":"Unsupervised Camouflaged Object Segmentation as Domain Adaptation","date":"2023-08-08","arxiv_id":"2308.04528","repositories_listed":1,"syntology":null},{"url":"/paper/xgbd-explanation-guided-graph-backdoor","slug":"xgbd-explanation-guided-graph-backdoor","title":"XGBD: Explanation-Guided Graph Backdoor Detection","date":"2023-08-08","arxiv_id":"2308.04406","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/xgbd-explanation-guided-graph-backdoor#ran","syntology_url":"https://syntology.ai/paper/2308.04406","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.04406"}},"official":{"repos":["guanzihan/gnn_backdoor_detection"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/soilnet-an-attention-based-spatio-temporal","slug":"soilnet-an-attention-based-spatio-temporal","title":"SSL-SoilNet: A Hybrid Transformer-based Framework with Self-Supervised Learning for Large-scale Soil Organic Carbon Prediction","date":"2023-08-07","arxiv_id":"2308.03586","repositories_listed":1,"syntology":null},{"url":"/paper/elucidate-gender-fairness-in-singing-voice","slug":"elucidate-gender-fairness-in-singing-voice","title":"Elucidate Gender Fairness in Singing Voice Transcription","date":"2023-08-05","arxiv_id":"2308.02898","repositories_listed":1,"syntology":null},{"url":"/paper/where-and-how-mitigating-confusion-in-neural","slug":"where-and-how-mitigating-confusion-in-neural","title":"Where and How: Mitigating Confusion in Neural Radiance Fields from Sparse Inputs","date":"2023-08-05","arxiv_id":"2308.02908","repositories_listed":1,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":8,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":10,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/where-and-how-mitigating-confusion-in-neural#ran","syntology_url":"https://syntology.ai/paper/2308.02908","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.02908"}},"official":{"repos":["bbbbby-99/wah-nerf"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/eyelids-intrinsic-motion-aware-feature","slug":"eyelids-intrinsic-motion-aware-feature","title":"Eyelid’s Intrinsic Motion-aware Feature Learning for Real-time Eyeblink Detection in the Wild","date":"2023-08-03","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/zero-shot-learning-by-harnessing-adversarial","slug":"zero-shot-learning-by-harnessing-adversarial","title":"Zero-Shot Learning by Harnessing Adversarial Samples","date":"2023-08-01","arxiv_id":"2308.00313","repositories_listed":1,"syntology":null},{"url":"/paper/styleprompter-all-styles-need-is-attention","slug":"styleprompter-all-styles-need-is-attention","title":"StylePrompter: All Styles Need Is Attention","date":"2023-07-30","arxiv_id":"2307.16151","repositories_listed":1,"syntology":null},{"url":"/paper/fingerprints-of-generative-models-in-the","slug":"fingerprints-of-generative-models-in-the","title":"Model Synthesis for Zero-Shot Model Attribution","date":"2023-07-29","arxiv_id":"2307.15977","repositories_listed":1,"syntology":null},{"url":"/paper/auto-tables-synthesizing-multi-step","slug":"auto-tables-synthesizing-multi-step","title":"Auto-Tables: Synthesizing Multi-Step Transformations to Relationalize Tables without Using Examples","date":"2023-07-27","arxiv_id":"2307.14565","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":3,"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/auto-tables-synthesizing-multi-step#ran","syntology_url":"https://syntology.ai/paper/2307.14565","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.14565"}},"official":{"repos":["lipengcs/auto-tables-benchmark"],"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/verifiable-feature-attributions-a-bridge","slug":"verifiable-feature-attributions-a-bridge","title":"Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability","date":"2023-07-27","arxiv_id":"2307.15007","repositories_listed":1,"syntology":null},{"url":"/paper/3d-semantic-subspace-traverser-empowering-3d","slug":"3d-semantic-subspace-traverser-empowering-3d","title":"3D Semantic Subspace Traverser: Empowering 3D Generative Model with Shape Editing Capability","date":"2023-07-26","arxiv_id":"2307.14051","repositories_listed":1,"syntology":null},{"url":"/paper/an-empirical-study-on-fairness-improvement","slug":"an-empirical-study-on-fairness-improvement","title":"Fairness Improvement with Multiple Protected Attributes: How Far Are We?","date":"2023-07-25","arxiv_id":"2308.01923","repositories_listed":1,"syntology":null},{"url":"/paper/holistic-exploration-on-universal","slug":"holistic-exploration-on-universal","title":"Holistic Exploration on Universal Decompositional Semantic Parsing: Architecture, Data Augmentation, and LLM Paradigm","date":"2023-07-25","arxiv_id":"2307.13424","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"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) · 0 unverified","sample_list":"/paper/holistic-exploration-on-universal#ran","syntology_url":"https://syntology.ai/paper/2307.13424","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.13424"}},"official":{"repos":["hexuandeng/hexp4uds"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/fairness-under-demographic-scarce-regime","slug":"fairness-under-demographic-scarce-regime","title":"Fairness Under Demographic Scarce Regime","date":"2023-07-24","arxiv_id":"2307.13081","repositories_listed":1,"syntology":null},{"url":"/paper/collaborative-graph-neural-networks-for","slug":"collaborative-graph-neural-networks-for","title":"Collaborative Graph Neural Networks for Attributed Network Embedding","date":"2023-07-22","arxiv_id":"2307.11981","repositories_listed":1,"syntology":null},{"url":"/paper/spectral-normalized-cut-graph-partitioning","slug":"spectral-normalized-cut-graph-partitioning","title":"Spectral Normalized-Cut Graph Partitioning with Fairness Constraints","date":"2023-07-22","arxiv_id":"2307.12065","repositories_listed":1,"syntology":null},{"url":"/paper/divide-bind-your-attention-for-improved","slug":"divide-bind-your-attention-for-improved","title":"Divide & Bind Your Attention for Improved Generative Semantic Nursing","date":"2023-07-20","arxiv_id":"2307.10864","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"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 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) · 1 unverified","sample_list":"/paper/divide-bind-your-attention-for-improved#ran","syntology_url":"https://syntology.ai/paper/2307.10864","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.10864"}},"official":{"repos":["boschresearch/Divide-and-Bind"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/a-siamese-based-verification-system-for-open","slug":"a-siamese-based-verification-system-for-open","title":"A Siamese-based Verification System for Open-set Architecture Attribution of Synthetic Images","date":"2023-07-19","arxiv_id":"2307.09822","repositories_listed":1,"syntology":null},{"url":"/paper/divert-more-attention-to-vision-language-1","slug":"divert-more-attention-to-vision-language-1","title":"Divert More Attention to Vision-Language Object Tracking","date":"2023-07-19","arxiv_id":"2307.10046","repositories_listed":1,"syntology":null},{"url":"/paper/shiftnas-improving-one-shot-nas-via","slug":"shiftnas-improving-one-shot-nas-via","title":"ShiftNAS: Improving One-shot NAS via Probability Shift","date":"2023-07-17","arxiv_id":"2307.08300","repositories_listed":1,"syntology":null},{"url":"/paper/towards-understanding-adversarial","slug":"towards-understanding-adversarial","title":"Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability","date":"2023-07-15","arxiv_id":"2307.07873","repositories_listed":1,"syntology":{"n":15,"n_ran":12,"n_constructed":0,"n_ran_checked":9,"n_instrument":3,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":7,"phrase":"12 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; 3 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/towards-understanding-adversarial#ran","syntology_url":"https://syntology.ai/paper/2307.07873","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.07873"}},"official":{"repos":["cgcl-codes/transferattacksurrogates"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/a-testing-based-approach-to-assess-the","slug":"a-testing-based-approach-to-assess-the","title":"Clusterability test for categorical data","date":"2023-07-14","arxiv_id":"2307.07346","repositories_listed":1,"syntology":null},{"url":"/paper/generating-efficient-training-data-via-llm","slug":"generating-efficient-training-data-via-llm","title":"Controllable Data Augmentation for Few-Shot Text Mining with Chain-of-Thought Attribute Manipulation","date":"2023-07-14","arxiv_id":"2307.07099","repositories_listed":1,"syntology":null},{"url":"/paper/leveraging-vision-language-foundation-models","slug":"leveraging-vision-language-foundation-models","title":"Leveraging Vision-Language Foundation Models for Fine-Grained Downstream Tasks","date":"2023-07-13","arxiv_id":"2307.06795","repositories_listed":1,"syntology":null},{"url":"/paper/t2i-compbench-a-comprehensive-benchmark-for-1","slug":"t2i-compbench-a-comprehensive-benchmark-for-1","title":"T2I-CompBench: A Comprehensive Benchmark for Open-world Compositional Text-to-image Generation","date":"2023-07-12","arxiv_id":"2307.06350","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":0,"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/t2i-compbench-a-comprehensive-benchmark-for-1#ran","syntology_url":"https://syntology.ai/paper/2307.06350","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.06350"}},"official":null}},{"url":"/paper/exfacegan-exploring-identity-directions-in","slug":"exfacegan-exploring-identity-directions-in","title":"ExFaceGAN: Exploring Identity Directions in GAN's Learned Latent Space for Synthetic Identity Generation","date":"2023-07-11","arxiv_id":"2307.05151","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 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; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/exfacegan-exploring-identity-directions-in#ran","syntology_url":"https://syntology.ai/paper/2307.05151","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.05151"}},"official":{"repos":["fdbtrs/exfacegan"],"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/histopathology-whole-slide-image-analysis-1","slug":"histopathology-whole-slide-image-analysis-1","title":"Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning","date":"2023-07-09","arxiv_id":"2307.04189","repositories_listed":1,"syntology":{"n":6,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":6,"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) · 3 unverified","sample_list":"/paper/histopathology-whole-slide-image-analysis-1#ran","syntology_url":"https://syntology.ai/paper/2307.04189","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.04189"}},"official":{"repos":["hku-medai/wsi-hgnn"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/synthesizing-forestry-images-conditioned-on","slug":"synthesizing-forestry-images-conditioned-on","title":"Synthesizing Forestry Images Conditioned on Plant Phenotype Using a Generative Adversarial Network","date":"2023-07-07","arxiv_id":"2307.03789","repositories_listed":1,"syntology":null},{"url":"/paper/preadd-prefix-adaptive-decoding-for","slug":"preadd-prefix-adaptive-decoding-for","title":"PREADD: Prefix-Adaptive Decoding for Controlled Text Generation","date":"2023-07-06","arxiv_id":"2307.03214","repositories_listed":1,"syntology":{"n":12,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":6,"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) · 6 unverified","sample_list":"/paper/preadd-prefix-adaptive-decoding-for#ran","syntology_url":"https://syntology.ai/paper/2307.03214","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.03214"}},"official":{"repos":["jonnypei/acl23-preadd"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":6,"ran_from_kinds":["official"]}}},{"url":"/paper/when-fair-classification-meets-noisy","slug":"when-fair-classification-meets-noisy","title":"When Fair Classification Meets Noisy Protected Attributes","date":"2023-07-06","arxiv_id":"2307.03306","repositories_listed":1,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":6,"n_instrument":3,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":10,"phrase":"9 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; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/when-fair-classification-meets-noisy#ran","syntology_url":"https://syntology.ai/paper/2307.03306","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.03306"}},"official":{"repos":["evijit/awareness_vs_unawareness"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/mitigating-the-learning-bias-towards","slug":"mitigating-the-learning-bias-towards","title":"Mitigating the Learning Bias towards Repetition by Self-Contrastive Training for Open-Ended Generation","date":"2023-07-04","arxiv_id":"2307.01542","repositories_listed":1,"syntology":null},{"url":"/paper/emogen-eliminating-subjective-bias-in","slug":"emogen-eliminating-subjective-bias-in","title":"EmoGen: Eliminating Subjective Bias in Emotional Music Generation","date":"2023-07-03","arxiv_id":"2307.01229","repositories_listed":1,"syntology":null},{"url":"/paper/trainable-transformer-in-transformer","slug":"trainable-transformer-in-transformer","title":"Trainable Transformer in Transformer","date":"2023-07-03","arxiv_id":"2307.01189","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"0 ran · 1 unverified","sample_list":"/paper/trainable-transformer-in-transformer#ran","syntology_url":"https://syntology.ai/paper/2307.01189","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2307.01189"}},"official":{"repos":["abhishekpanigrahi1996/transformer_in_transformer"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/seeing-is-not-believing-an-identity-hider-for","slug":"seeing-is-not-believing-an-identity-hider-for","title":"Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection","date":"2023-07-02","arxiv_id":"2307.00481","repositories_listed":1,"syntology":null},{"url":"/paper/beyond-neural-on-neural-approaches-to-speaker","slug":"beyond-neural-on-neural-approaches-to-speaker","title":"Beyond Neural-on-Neural Approaches to Speaker Gender Protection","date":"2023-06-30","arxiv_id":"2306.17700","repositories_listed":1,"syntology":null},{"url":"/paper/large-language-model-as-attributed-training-1","slug":"large-language-model-as-attributed-training-1","title":"Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias","date":"2023-06-28","arxiv_id":"2306.15895","repositories_listed":1,"syntology":{"n":17,"n_ran":12,"n_constructed":0,"n_ran_checked":8,"n_instrument":4,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":2,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 4 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/large-language-model-as-attributed-training-1#ran","syntology_url":"https://syntology.ai/paper/2306.15895","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.15895"}},"official":{"repos":["yueyu1030/attrprompt"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/pfb-diff-progressive-feature-blending","slug":"pfb-diff-progressive-feature-blending","title":"PFB-Diff: Progressive Feature Blending Diffusion for Text-driven Image Editing","date":"2023-06-28","arxiv_id":"2306.16894","repositories_listed":1,"syntology":null},{"url":"/paper/multi-task-item-attribute-graph-pre-training","slug":"multi-task-item-attribute-graph-pre-training","title":"Multi-task Item-attribute Graph Pre-training for Strict Cold-start Item Recommendation","date":"2023-06-26","arxiv_id":"2306.14462","repositories_listed":1,"syntology":null},{"url":"/paper/product-information-extraction-using-chatgpt","slug":"product-information-extraction-using-chatgpt","title":"Product Information Extraction using ChatGPT","date":"2023-06-23","arxiv_id":"2306.14921","repositories_listed":1,"syntology":null},{"url":"/paper/wbcatt-a-white-blood-cell-dataset-annotated-1","slug":"wbcatt-a-white-blood-cell-dataset-annotated-1","title":"WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological Attributes","date":"2023-06-23","arxiv_id":"2306.13531","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":1,"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) · 1 unverified","sample_list":"/paper/wbcatt-a-white-blood-cell-dataset-annotated-1#ran","syntology_url":"https://syntology.ai/paper/2306.13531","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.13531"}},"official":{"repos":["apple2373/wbcatt"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/evading-forensic-classifiers-with-attribute-1","slug":"evading-forensic-classifiers-with-attribute-1","title":"Evading Forensic Classifiers with Attribute-Conditioned Adversarial Faces","date":"2023-06-22","arxiv_id":"2306.13091","repositories_listed":1,"syntology":{"n":20,"n_ran":12,"n_constructed":7,"n_ran_checked":9,"n_instrument":3,"n_unverified":8,"n_honours":0,"n_violates":0,"n_no_contract":9,"n_pointer_only":20,"phrase":"12 ran (of which 7 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 3 where Syntology's instrument failed) · 8 unverified","sample_list":"/paper/evading-forensic-classifiers-with-attribute-1#ran","syntology_url":"https://syntology.ai/paper/2306.13091","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.13091"}},"official":{"repos":["koushiksrivats/face_attribute_attack"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":7,"n_ran_no_instrument_failure":9,"n_unverified":8,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-enriched-controllability-for","slug":"towards-enriched-controllability-for","title":"Towards Enriched Controllability for Educational Question Generation","date":"2023-06-21","arxiv_id":"2306.14917","repositories_listed":1,"syntology":null},{"url":"/paper/cross-modal-attribute-insertions-for","slug":"cross-modal-attribute-insertions-for","title":"Cross-Modal Attribute Insertions for Assessing the Robustness of Vision-and-Language Learning","date":"2023-06-19","arxiv_id":"2306.11065","repositories_listed":1,"syntology":null},{"url":"/paper/seen-to-unseen-exploring-compositional","slug":"seen-to-unseen-exploring-compositional","title":"Seen to Unseen: Exploring Compositional Generalization of Multi-Attribute Controllable Dialogue Generation","date":"2023-06-17","arxiv_id":"2306.10317","repositories_listed":1,"syntology":null},{"url":"/paper/disasternets-embedding-machine-learning-in","slug":"disasternets-embedding-machine-learning-in","title":"DisasterNets: Embedding Machine Learning in Disaster Mapping","date":"2023-06-16","arxiv_id":"2306.09815","repositories_listed":1,"syntology":null},{"url":"/paper/compositional-prototypical-networks-for-few","slug":"compositional-prototypical-networks-for-few","title":"Compositional Prototypical Networks for Few-Shot Classification","date":"2023-06-11","arxiv_id":"2306.06584","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":3,"phrase":"1 ran (of which 1 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; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/compositional-prototypical-networks-for-few#ran","syntology_url":"https://syntology.ai/paper/2306.06584","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.06584"}},"official":{"repos":["fikry102/CPN"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/estimating-the-uncertainty-in-emotion","slug":"estimating-the-uncertainty-in-emotion","title":"Estimating the Uncertainty in Emotion Attributes using Deep Evidential Regression","date":"2023-06-11","arxiv_id":"2306.06760","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/estimating-the-uncertainty-in-emotion#ran","syntology_url":"https://syntology.ai/paper/2306.06760","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.06760"}},"official":{"repos":["w-wu/deer"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/self-enhancement-improves-text-image","slug":"self-enhancement-improves-text-image","title":"Self-Enhancement Improves Text-Image Retrieval in Foundation Visual-Language Models","date":"2023-06-11","arxiv_id":"2306.06691","repositories_listed":1,"syntology":null},{"url":"/paper/courier-contrastive-user-intention","slug":"courier-contrastive-user-intention","title":"COURIER: Contrastive User Intention Reconstruction for Large-Scale Visual Recommendation","date":"2023-06-08","arxiv_id":"2306.05001","repositories_listed":1,"syntology":null},{"url":"/paper/allophant-cross-lingual-phoneme-recognition","slug":"allophant-cross-lingual-phoneme-recognition","title":"Allophant: Cross-lingual Phoneme Recognition with Articulatory Attributes","date":"2023-06-07","arxiv_id":"2306.04306","repositories_listed":1,"syntology":null},{"url":"/paper/long-sequence-hopfield-memory","slug":"long-sequence-hopfield-memory","title":"Long Sequence Hopfield Memory","date":"2023-06-07","arxiv_id":"2306.04532","repositories_listed":1,"syntology":null},{"url":"/paper/m-3-fair-mitigating-bias-in-healthcare-data","slug":"m-3-fair-mitigating-bias-in-healthcare-data","title":"M$^3$Fair: Mitigating Bias in Healthcare Data through Multi-Level and Multi-Sensitive-Attribute Reweighting Method","date":"2023-06-07","arxiv_id":"2306.04118","repositories_listed":1,"syntology":null},{"url":"/paper/bioblp-a-modular-framework-for-learning-on","slug":"bioblp-a-modular-framework-for-learning-on","title":"BioBLP: A Modular Framework for Learning on Multimodal Biomedical Knowledge Graphs","date":"2023-06-06","arxiv_id":"2306.03606","repositories_listed":1,"syntology":null},{"url":"/paper/a-large-scale-study-of-probabilistic","slug":"a-large-scale-study-of-probabilistic","title":"A Large-Scale Study of Probabilistic Calibration in Neural Network Regression","date":"2023-06-05","arxiv_id":"2306.02738","repositories_listed":1,"syntology":{"n":7,"n_ran":6,"n_constructed":0,"n_ran_checked":0,"n_instrument":6,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":7,"phrase":"6 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; 6 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/a-large-scale-study-of-probabilistic#ran","syntology_url":"https://syntology.ai/paper/2306.02738","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.02738"}},"official":{"repos":["vekteur/probabilistic-calibration-study"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"url":"/paper/navigating-explanatory-multiverse-through","slug":"navigating-explanatory-multiverse-through","title":"Navigating Explanatory Multiverse Through Counterfactual Path Geometry","date":"2023-06-05","arxiv_id":"2306.02786","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 1 unverified","sample_list":"/paper/navigating-explanatory-multiverse-through#ran","syntology_url":"https://syntology.ai/paper/2306.02786","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.02786"}},"official":{"repos":["xuanxuanxuan-git/facelift"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/structural-re-weighting-improves-graph-domain","slug":"structural-re-weighting-improves-graph-domain","title":"Structural Re-weighting Improves Graph Domain Adaptation","date":"2023-06-05","arxiv_id":"2306.03221","repositories_listed":1,"syntology":{"n":7,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":5,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":7,"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) · 5 unverified","sample_list":"/paper/structural-re-weighting-improves-graph-domain#ran","syntology_url":"https://syntology.ai/paper/2306.03221","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.03221"}},"official":{"repos":["graph-com/strurw"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-unified-text-based-person-retrieval-a","slug":"towards-unified-text-based-person-retrieval-a","title":"Towards Unified Text-based Person Retrieval: A Large-scale Multi-Attribute and Language Search Benchmark","date":"2023-06-05","arxiv_id":"2306.02898","repositories_listed":1,"syntology":{"n":12,"n_ran":9,"n_constructed":0,"n_ran_checked":4,"n_instrument":5,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":2,"phrase":"9 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; 5 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/towards-unified-text-based-person-retrieval-a#ran","syntology_url":"https://syntology.ai/paper/2306.02898","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.02898"}},"official":{"repos":["Shuyu-XJTU/APTM"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/affinity-clustering-framework-for-data","slug":"affinity-clustering-framework-for-data","title":"Affinity Clustering Framework for Data Debiasing Using Pairwise Distribution Discrepancy","date":"2023-06-02","arxiv_id":"2306.01699","repositories_listed":1,"syntology":null},{"url":"/paper/conditional-generation-from-unconditional","slug":"conditional-generation-from-unconditional","title":"Conditional Generation from Unconditional Diffusion Models using Denoiser Representations","date":"2023-06-02","arxiv_id":"2306.01900","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 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; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/conditional-generation-from-unconditional#ran","syntology_url":"https://syntology.ai/paper/2306.01900","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.01900"}},"official":{"repos":["cvlab-stonybrook/fewshot-conditional-diffusion"],"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/knowledge-graph-reasoning-over-entities-and","slug":"knowledge-graph-reasoning-over-entities-and","title":"Knowledge Graph Reasoning over Entities and Numerical Values","date":"2023-06-02","arxiv_id":"2306.01399","repositories_listed":1,"syntology":null},{"url":"/paper/tackling-unbounded-state-spaces-in-continuing","slug":"tackling-unbounded-state-spaces-in-continuing","title":"Learning to Stabilize Online Reinforcement Learning in Unbounded State Spaces","date":"2023-06-02","arxiv_id":"2306.01896","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":1,"n_ran_checked":5,"n_instrument":1,"n_unverified":0,"n_honours":2,"n_violates":2,"n_no_contract":1,"n_pointer_only":6,"phrase":"6 ran (of which 1 constructed an object rather than computing a result; 5 with no instrument failure: 2 honoured, 2 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/tackling-unbounded-state-spaces-in-continuing#ran","syntology_url":"https://syntology.ai/paper/2306.01896","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2306.01896"}},"official":{"repos":["badger-rl/stop"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":1,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/improving-and-benchmarking-offline","slug":"improving-and-benchmarking-offline","title":"Improving and Benchmarking Offline Reinforcement Learning Algorithms","date":"2023-06-01","arxiv_id":"2306.00972","repositories_listed":1,"syntology":null},{"url":"/paper/an-invariant-learning-characterization-of","slug":"an-invariant-learning-characterization-of","title":"An Invariant Learning Characterization of Controlled Text Generation","date":"2023-05-31","arxiv_id":"2306.00198","repositories_listed":1,"syntology":null},{"url":"/paper/controlled-text-generation-with-hidden","slug":"controlled-text-generation-with-hidden","title":"Controlled Text Generation with Hidden Representation Transformations","date":"2023-05-30","arxiv_id":"2305.19230","repositories_listed":1,"syntology":null},{"url":"/paper/learning-conditional-attributes-for-1","slug":"learning-conditional-attributes-for-1","title":"Learning Conditional Attributes for Compositional Zero-Shot Learning","date":"2023-05-29","arxiv_id":"2305.17940","repositories_listed":1,"syntology":{"n":9,"n_ran":6,"n_constructed":4,"n_ran_checked":4,"n_instrument":2,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":9,"phrase":"6 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; 2 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/learning-conditional-attributes-for-1#ran","syntology_url":"https://syntology.ai/paper/2305.17940","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2305.17940"}},"official":{"repos":["wqshmzh/canet-czsl"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/td-gem-text-driven-garment-editing-mapper","slug":"td-gem-text-driven-garment-editing-mapper","title":"TD-GEM: Text-Driven Garment Editing Mapper","date":"2023-05-29","arxiv_id":"2305.18120","repositories_listed":1,"syntology":null},{"url":"/paper/vlsd-an-efficient-subgroup-discovery","slug":"vlsd-an-efficient-subgroup-discovery","title":"VLSD—An Efficient Subgroup Discovery Algorithm Based on Equivalence Classes and Optimistic Estimate","date":"2023-05-29","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/fusecap-leveraging-large-language-models-to","slug":"fusecap-leveraging-large-language-models-to","title":"FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions","date":"2023-05-28","arxiv_id":"2305.17718","repositories_listed":1,"syntology":null},{"url":"/paper/schema-guided-user-satisfaction-modeling-for","slug":"schema-guided-user-satisfaction-modeling-for","title":"Schema-Guided User Satisfaction Modeling for Task-Oriented Dialogues","date":"2023-05-26","arxiv_id":"2305.16798","repositories_listed":1,"syntology":null},{"url":"/paper/towards-open-world-product-attribute-mining-a","slug":"towards-open-world-product-attribute-mining-a","title":"Towards Open-World Product Attribute Mining: A Lightly-Supervised Approach","date":"2023-05-26","arxiv_id":"2305.18350","repositories_listed":1,"syntology":null}],"record_sha256":"7293cec2f31971f3490987dd689b255d5a11993a403ed73a9dbb994eadf0436a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}