{"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/zero-shot-learning/papers/7","list_of":"/task/zero-shot-learning","task":"Zero-Shot Learning","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":7,"pages_in_order":19,"rows_per_page":100,"rows":[601,700],"of":1864,"counts":{"archive_papers_tagged":1864,"with_a_code_link":787,"where_syntology_ran_a_sample":245,"not_listed_spam_title":0,"listed":1864,"listed_where_code_ran":245,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":204,"every_run_a_failure_of_syntologys_instrument":41,"listed_with_a_run_with_no_instrument_failure":204,"listed_every_run_a_failure_of_syntologys_instrument":41,"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/zero-shot-learning","prev":"/task/zero-shot-learning/papers/6","next":"/task/zero-shot-learning/papers/8","papers":[{"url":"/paper/data-efficient-language-supervised-zero-shot-2","slug":"data-efficient-language-supervised-zero-shot-2","title":"Data Efficient Language-supervised Zero-shot Recognition with Optimal Transport Distillation","date":"2021-12-17","arxiv_id":"2112.09445","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/data-efficient-language-supervised-zero-shot-2#ran","syntology_url":"https://syntology.ai/paper/2112.09445","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.09445"}},"official":{"repos":["facebookresearch/otter"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/extreme-zero-shot-learning-for-extreme-text","slug":"extreme-zero-shot-learning-for-extreme-text","title":"Extreme Zero-Shot Learning for Extreme Text Classification","date":"2021-12-16","arxiv_id":"2112.08652","repositories_listed":1,"syntology":null},{"url":"/paper/transzero-cross-attribute-guided-transformer","slug":"transzero-cross-attribute-guided-transformer","title":"TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning","date":"2021-12-16","arxiv_id":"2112.08643","repositories_listed":1,"syntology":null},{"url":"/paper/decoupling-zero-shot-semantic-segmentation","slug":"decoupling-zero-shot-semantic-segmentation","title":"Decoupling Zero-Shot Semantic Segmentation","date":"2021-12-15","arxiv_id":"2112.07910","repositories_listed":1,"syntology":null},{"url":"/paper/clip-lite-information-efficient-visual","slug":"clip-lite-information-efficient-visual","title":"CLIP-Lite: Information Efficient Visual Representation Learning with Language Supervision","date":"2021-12-14","arxiv_id":"2112.07133","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_constructed":0,"n_ran_checked":5,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":1,"phrase":"7 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/clip-lite-information-efficient-visual#ran","syntology_url":"https://syntology.ai/paper/2112.07133","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2112.07133"}},"official":{"repos":["4m4n5/CLIP-Lite"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/transzero-attribute-guided-transformer-for","slug":"transzero-attribute-guided-transformer-for","title":"TransZero: Attribute-guided Transformer for Zero-Shot Learning","date":"2021-12-03","arxiv_id":"2112.01683","repositories_listed":1,"syntology":null},{"url":"/paper/zero-shot-image-to-text-generation-for-visual","slug":"zero-shot-image-to-text-generation-for-visual","title":"ZeroCap: Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic","date":"2021-11-29","arxiv_id":"2111.14447","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/zero-shot-image-to-text-generation-for-visual#ran","syntology_url":"https://syntology.ai/paper/2111.14447","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.14447"}},"official":{"repos":["yoadtew/zero-shot-image-to-text"],"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/zero-shot-learning-of-continuous-3d","slug":"zero-shot-learning-of-continuous-3d","title":"Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fields","date":"2021-11-27","arxiv_id":"2112.00002","repositories_listed":1,"syntology":null},{"url":"/paper/amortized-prompt-lightweight-fine-tuning-for","slug":"amortized-prompt-lightweight-fine-tuning-for","title":"Domain Prompt Learning for Efficiently Adapting CLIP to Unseen Domains","date":"2021-11-25","arxiv_id":"2111.12853","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":1,"n_no_contract":7,"n_pointer_only":17,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 1 violated, 7 with no contract checked; 4 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/amortized-prompt-lightweight-fine-tuning-for#ran","syntology_url":"https://syntology.ai/paper/2111.12853","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.12853"}},"official":{"repos":["shogi880/DPLCLIP"],"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/ml-decoder-scalable-and-versatile","slug":"ml-decoder-scalable-and-versatile","title":"ML-Decoder: Scalable and Versatile Classification Head","date":"2021-11-25","arxiv_id":"2111.12933","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"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) · 1 unverified","sample_list":"/paper/ml-decoder-scalable-and-versatile#ran","syntology_url":"https://syntology.ai/paper/2111.12933","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2111.12933"}},"official":{"repos":["alibaba-miil/ml_decoder"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/zero-shot-learning-in-named-entity","slug":"zero-shot-learning-in-named-entity","title":"Zero-Shot Learning in Named-Entity Recognition with External Knowledge","date":"2021-11-15","arxiv_id":"2111.07734","repositories_listed":1,"syntology":null},{"url":"/paper/zero-shot-information-extraction-to-enhance-a","slug":"zero-shot-information-extraction-to-enhance-a","title":"Zero-Shot Information Extraction to Enhance a Knowledge Graph Describing Silk Textiles","date":"2021-11-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/wav2clip-learning-robust-audio","slug":"wav2clip-learning-robust-audio","title":"Wav2CLIP: Learning Robust Audio Representations From CLIP","date":"2021-10-21","arxiv_id":"2110.11499","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":0,"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/wav2clip-learning-robust-audio#ran","syntology_url":"https://syntology.ai/paper/2110.11499","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.11499"}},"official":{"repos":["descriptinc/lyrebird-wav2clip"],"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/learning-single-multi-attribute-of-object","slug":"learning-single-multi-attribute-of-object","title":"Learning Single/Multi-Attribute of Object with Symmetry and Group","date":"2021-10-09","arxiv_id":"2110.04603","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/learning-single-multi-attribute-of-object#ran","syntology_url":"https://syntology.ai/paper/2110.04603","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.04603"}},"official":{"repos":["DirtyHarryLYL/SymNet"],"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/zspeedl-evaluating-the-performance-of-zero","slug":"zspeedl-evaluating-the-performance-of-zero","title":"ZSpeedL -- Evaluating the Performance of Zero-Shot Learning Methods using Low-Power Devices","date":"2021-10-09","arxiv_id":"2110.04535","repositories_listed":1,"syntology":null},{"url":"/paper/bridge-to-target-domain-by-prototypical","slug":"bridge-to-target-domain-by-prototypical","title":"Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot Filling","date":"2021-10-07","arxiv_id":"2110.03572","repositories_listed":1,"syntology":null},{"url":"/paper/semantic-guided-zero-shot-learning-for-low","slug":"semantic-guided-zero-shot-learning-for-low","title":"Semantic-Guided Zero-Shot Learning for Low-Light Image/Video Enhancement","date":"2021-10-03","arxiv_id":"2110.00970","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":8,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":8,"n_pointer_only":0,"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) · 1 unverified","sample_list":"/paper/semantic-guided-zero-shot-learning-for-low#ran","syntology_url":"https://syntology.ai/paper/2110.00970","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2110.00970"}},"official":{"repos":["ShenZheng2000/Semantic-Guided-Low-Light-Image-Enhancement"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/implicit-and-explicit-attention-for-zero-shot","slug":"implicit-and-explicit-attention-for-zero-shot","title":"Implicit and Explicit Attention for Zero-Shot Learning","date":"2021-10-02","arxiv_id":"2110.00860","repositories_listed":1,"syntology":null},{"url":"/paper/closed-form-sample-probing-for-learning","slug":"closed-form-sample-probing-for-learning","title":"Closed-form Sample Probing for Learning Generative Models in Zero-shot Learning","date":"2021-09-29","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/fine-grained-zero-shot-learning-with-dna-as","slug":"fine-grained-zero-shot-learning-with-dna-as","title":"Fine-Grained Zero-Shot Learning with DNA as Side Information","date":"2021-09-29","arxiv_id":"2109.14133","repositories_listed":1,"syntology":null},{"url":"/paper/exploring-a-unified-sequence-to-sequence","slug":"exploring-a-unified-sequence-to-sequence","title":"Exploring a Unified Sequence-To-Sequence Transformer for Medical Product Safety Monitoring in Social Media","date":"2021-09-13","arxiv_id":"2109.05815","repositories_listed":1,"syntology":null},{"url":"/paper/field-guide-inspired-zero-shot-learning","slug":"field-guide-inspired-zero-shot-learning","title":"Field-Guide-Inspired Zero-Shot Learning","date":"2021-08-24","arxiv_id":"2108.10967","repositories_listed":1,"syntology":null},{"url":"/paper/discriminative-region-based-multi-label-zero","slug":"discriminative-region-based-multi-label-zero","title":"Discriminative Region-based Multi-Label Zero-Shot Learning","date":"2021-08-20","arxiv_id":"2108.09301","repositories_listed":1,"syntology":{"n":7,"n_ran":7,"n_constructed":4,"n_ran_checked":6,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"7 ran (of which 4 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) · 0 unverified","sample_list":"/paper/discriminative-region-based-multi-label-zero#ran","syntology_url":"https://syntology.ai/paper/2108.09301","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.09301"}},"official":{"repos":["akshitac8/biam"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":4,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/contrastive-language-image-pre-training-for","slug":"contrastive-language-image-pre-training-for","title":"Contrastive Language-Image Pre-training for the Italian Language","date":"2021-08-19","arxiv_id":"2108.08688","repositories_listed":1,"syntology":null},{"url":"/paper/generative-zero-shot-learning-for-semantic","slug":"generative-zero-shot-learning-for-semantic","title":"Generative Zero-Shot Learning for Semantic Segmentation of 3D Point Clouds","date":"2021-08-13","arxiv_id":"2108.06230","repositories_listed":1,"syntology":null},{"url":"/paper/relation-aware-compositional-zero-shot","slug":"relation-aware-compositional-zero-shot","title":"Relation-aware Compositional Zero-shot Learning for Attribute-Object Pair Recognition","date":"2021-08-10","arxiv_id":"2108.04603","repositories_listed":1,"syntology":null},{"url":"/paper/a-unified-model-for-zero-shot-music-source","slug":"a-unified-model-for-zero-shot-music-source","title":"A Unified Model for Zero-shot Music Source Separation, Transcription and Synthesis","date":"2021-08-07","arxiv_id":"2108.03456","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":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) · 3 unverified","sample_list":"/paper/a-unified-model-for-zero-shot-music-source#ran","syntology_url":"https://syntology.ai/paper/2108.03456","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.03456"}},"official":{"repos":["kikyo-16/a-unified-model-for-zero-shot-musical-source-separation-transcription-and-synthesis"],"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/elaborative-rehearsal-for-zero-shot-action","slug":"elaborative-rehearsal-for-zero-shot-action","title":"Elaborative Rehearsal for Zero-shot Action Recognition","date":"2021-08-05","arxiv_id":"2108.02833","repositories_listed":1,"syntology":{"n":15,"n_ran":10,"n_constructed":0,"n_ran_checked":8,"n_instrument":2,"n_unverified":5,"n_honours":0,"n_violates":1,"n_no_contract":7,"n_pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 1 violated, 7 with no contract checked; 2 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/elaborative-rehearsal-for-zero-shot-action#ran","syntology_url":"https://syntology.ai/paper/2108.02833","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.02833"}},"official":{"repos":["DeLightCMU/ElaborativeRehearsal"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/free-feature-refinement-for-generalized-zero","slug":"free-feature-refinement-for-generalized-zero","title":"FREE: Feature Refinement for Generalized Zero-Shot Learning","date":"2021-07-29","arxiv_id":"2107.13807","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":1,"n_ran_checked":1,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/free-feature-refinement-for-generalized-zero#ran","syntology_url":"https://syntology.ai/paper/2107.13807","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.13807"}},"official":{"repos":["shiming-chen/FREE"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/pre-train-prompt-and-predict-a-systematic","slug":"pre-train-prompt-and-predict-a-systematic","title":"Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing","date":"2021-07-28","arxiv_id":"2107.13586","repositories_listed":1,"syntology":null},{"url":"/paper/a-new-split-for-evaluating-true-zero-shot","slug":"a-new-split-for-evaluating-true-zero-shot","title":"A New Split for Evaluating True Zero-Shot Action Recognition","date":"2021-07-27","arxiv_id":"2107.13029","repositories_listed":1,"syntology":null},{"url":"/paper/fewclue-a-chinese-few-shot-learning","slug":"fewclue-a-chinese-few-shot-learning","title":"FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark","date":"2021-07-15","arxiv_id":"2107.07498","repositories_listed":1,"syntology":null},{"url":"/paper/multi-label-generalized-zero-shot-learning","slug":"multi-label-generalized-zero-shot-learning","title":"Multi-Label Generalized Zero Shot Learning for the Classification of Disease in Chest Radiographs","date":"2021-07-14","arxiv_id":"2107.06563","repositories_listed":1,"syntology":null},{"url":"/paper/mitigating-generation-shifts-for-generalized","slug":"mitigating-generation-shifts-for-generalized","title":"Mitigating Generation Shifts for Generalized Zero-Shot Learning","date":"2021-07-07","arxiv_id":"2107.03163","repositories_listed":1,"syntology":null},{"url":"/paper/ensemble-of-loss-functions-to-improve","slug":"ensemble-of-loss-functions-to-improve","title":"Ensemble of Loss Functions to Improve Generalizability of Deep Metric Learning methods","date":"2021-07-02","arxiv_id":"2107.01130","repositories_listed":1,"syntology":null},{"url":"/paper/zero-shot-learning-with-class-description","slug":"zero-shot-learning-with-class-description","title":"Zero-shot Learning with Class Description Regularization","date":"2021-06-30","arxiv_id":"2106.16108","repositories_listed":1,"syntology":null},{"url":"/paper/k-zsl-resources-for-knowledge-driven-zero","slug":"k-zsl-resources-for-knowledge-driven-zero","title":"Benchmarking Knowledge-driven Zero-shot Learning","date":"2021-06-29","arxiv_id":"2106.15047","repositories_listed":1,"syntology":null},{"url":"/paper/disentangling-semantic-to-visual-confusion","slug":"disentangling-semantic-to-visual-confusion","title":"Disentangling Semantic-to-visual Confusion for Zero-shot Learning","date":"2021-06-16","arxiv_id":"2106.08605","repositories_listed":1,"syntology":null},{"url":"/paper/a-framework-to-enhance-generalization-of-deep","slug":"a-framework-to-enhance-generalization-of-deep","title":"A Framework to Enhance Generalization of Deep Metric Learning methods using General Discriminative Feature Learning and Class Adversarial Neural Networks","date":"2021-06-11","arxiv_id":"2106.06420","repositories_listed":1,"syntology":null},{"url":"/paper/towards-user-driven-neural-machine","slug":"towards-user-driven-neural-machine","title":"Towards User-Driven Neural Machine Translation","date":"2021-06-11","arxiv_id":"2106.06200","repositories_listed":1,"syntology":null},{"url":"/paper/multilingual-neural-semantic-parsing-for-low","slug":"multilingual-neural-semantic-parsing-for-low","title":"Multilingual Neural Semantic Parsing for Low-Resourced Languages","date":"2021-06-07","arxiv_id":"2106.03469","repositories_listed":1,"syntology":null},{"url":"/paper/hardness-sampling-for-self-training-based","slug":"hardness-sampling-for-self-training-based","title":"Hardness Sampling for Self-Training Based Transductive Zero-Shot Learning","date":"2021-06-01","arxiv_id":"2106.00264","repositories_listed":1,"syntology":null},{"url":"/paper/pho-sc-net-an-approach-towards-zero-shot-word","slug":"pho-sc-net-an-approach-towards-zero-shot-word","title":"Pho(SC)-CTC -- A Hybrid Approach Towards Zero-shot Word Image Recognition","date":"2021-05-31","arxiv_id":"2105.15093","repositories_listed":1,"syntology":null},{"url":"/paper/prsl-interpretable-multi-label-stacking-by","slug":"prsl-interpretable-multi-label-stacking-by","title":"pRSL: Interpretable Multi-label Stacking by Learning Probabilistic Rules","date":"2021-05-28","arxiv_id":"2105.13850","repositories_listed":1,"syntology":null},{"url":"/paper/semantic-diversity-learning-for-zero-shot","slug":"semantic-diversity-learning-for-zero-shot","title":"Semantic Diversity Learning for Zero-Shot Multi-label Classification","date":"2021-05-12","arxiv_id":"2105.05926","repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-vaes-with-generative-replay-for","slug":"dynamic-vaes-with-generative-replay-for","title":"Dynamic VAEs with Generative Replay for Continual Zero-shot Learning","date":"2021-04-26","arxiv_id":"2104.12468","repositories_listed":1,"syntology":null},{"url":"/paper/revisiting-document-representations-for-large","slug":"revisiting-document-representations-for-large","title":"Revisiting Document Representations for Large-Scale Zero-Shot Learning","date":"2021-04-21","arxiv_id":"2104.10355","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/revisiting-document-representations-for-large#ran","syntology_url":"https://syntology.ai/paper/2104.10355","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.10355"}},"official":{"repos":["heendung/vs-zsl"],"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/imaginative-walks-generative-random-walk","slug":"imaginative-walks-generative-random-walk","title":"Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning Representation","date":"2021-04-20","arxiv_id":"2104.09757","repositories_listed":1,"syntology":null},{"url":"/paper/americasnli-evaluating-zero-shot-natural","slug":"americasnli-evaluating-zero-shot-natural","title":"AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages","date":"2021-04-18","arxiv_id":"2104.08726","repositories_listed":1,"syntology":null},{"url":"/paper/does-language-help-generalization-in-vision","slug":"does-language-help-generalization-in-vision","title":"Does language help generalization in vision models?","date":"2021-04-16","arxiv_id":"2104.08313","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":0,"n_honours":2,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 2 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/does-language-help-generalization-in-vision#ran","syntology_url":"https://syntology.ai/paper/2104.08313","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2104.08313"}},"official":{"repos":["bdvllrs/generalization-vision"],"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/zero-shot-learning-on-3d-point-cloud-objects","slug":"zero-shot-learning-on-3d-point-cloud-objects","title":"Zero-Shot Learning on 3D Point Cloud Objects and Beyond","date":"2021-04-11","arxiv_id":"2104.04980","repositories_listed":1,"syntology":null},{"url":"/paper/meta-tuning-language-models-to-answer-prompts","slug":"meta-tuning-language-models-to-answer-prompts","title":"Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections","date":"2021-04-10","arxiv_id":"2104.04670","repositories_listed":1,"syntology":null},{"url":"/paper/modern-hopfield-networks-for-few-and-zero","slug":"modern-hopfield-networks-for-few-and-zero","title":"Modern Hopfield Networks for Few- and Zero-Shot Reaction Template Prediction","date":"2021-04-07","arxiv_id":"2104.03279","repositories_listed":1,"syntology":null},{"url":"/paper/finding-spoiler-bias-in-tweets-by-zero-shot","slug":"finding-spoiler-bias-in-tweets-by-zero-shot","title":"Finding Spoiler Bias in Tweets by Zero-shot Learning and Knowledge Distilling from Neural Text Simplification","date":"2021-04-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/towards-offensive-language-identification-for","slug":"towards-offensive-language-identification-for","title":"Towards Offensive Language Identification for Dravidian Languages","date":"2021-04-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/tf-gczsl-task-free-generalized-continual-zero","slug":"tf-gczsl-task-free-generalized-continual-zero","title":"Online Lifelong Generalized Zero-Shot Learning","date":"2021-03-19","arxiv_id":"2103.10741","repositories_listed":1,"syntology":null},{"url":"/paper/multilingual-code-switching-for-zero-shot","slug":"multilingual-code-switching-for-zero-shot","title":"Multilingual Code-Switching for Zero-Shot Cross-Lingual Intent Prediction and Slot Filling","date":"2021-03-13","arxiv_id":"2103.07792","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":2,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/multilingual-code-switching-for-zero-shot#ran","syntology_url":"https://syntology.ai/paper/2103.07792","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.07792"}},"official":{"repos":["jitinkrishnan/Multilingual-ZeroShot-SlotFilling"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/cooperative-learning-of-zero-shot-machine","slug":"cooperative-learning-of-zero-shot-machine","title":"Cooperative Self-training of Machine Reading Comprehension","date":"2021-03-12","arxiv_id":"2103.07449","repositories_listed":1,"syntology":null},{"url":"/paper/goal-oriented-gaze-estimation-for-zero-shot","slug":"goal-oriented-gaze-estimation-for-zero-shot","title":"Goal-Oriented Gaze Estimation for Zero-Shot Learning","date":"2021-03-05","arxiv_id":"2103.03433","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/goal-oriented-gaze-estimation-for-zero-shot#ran","syntology_url":"https://syntology.ai/paper/2103.03433","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2103.03433"}},"official":{"repos":["osierboy/GEM-ZSL"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/counterfactual-zero-shot-and-open-set-visual","slug":"counterfactual-zero-shot-and-open-set-visual","title":"Counterfactual Zero-Shot and Open-Set Visual Recognition","date":"2021-03-01","arxiv_id":"2103.00887","repositories_listed":1,"syntology":null},{"url":"/paper/knowledge-aware-zero-shot-learning-survey-and","slug":"knowledge-aware-zero-shot-learning-survey-and","title":"Knowledge-aware Zero-Shot Learning: Survey and Perspective","date":"2021-02-26","arxiv_id":"2103.00070","repositories_listed":1,"syntology":null},{"url":"/paper/ontozsl-ontology-enhanced-zero-shot-learning","slug":"ontozsl-ontology-enhanced-zero-shot-learning","title":"OntoZSL: Ontology-enhanced Zero-shot Learning","date":"2021-02-15","arxiv_id":"2102.07339","repositories_listed":1,"syntology":null},{"url":"/paper/end-to-end-generative-zero-shot-learning-via","slug":"end-to-end-generative-zero-shot-learning-via","title":"End-to-end Generative Zero-shot Learning via Few-shot Learning","date":"2021-02-08","arxiv_id":"2102.04379","repositories_listed":1,"syntology":null},{"url":"/paper/adversarial-training-of-variational-auto-1","slug":"adversarial-training-of-variational-auto-1","title":"Adversarial Training of Variational Auto-encoders for Continual Zero-shot Learning(A-CZSL)","date":"2021-02-07","arxiv_id":"2102.03778","repositories_listed":1,"syntology":null},{"url":"/paper/learning-graph-embeddings-for-compositional","slug":"learning-graph-embeddings-for-compositional","title":"Learning Graph Embeddings for Compositional Zero-shot Learning","date":"2021-02-03","arxiv_id":"2102.01987","repositories_listed":1,"syntology":{"n":11,"n_ran":6,"n_constructed":3,"n_ran_checked":3,"n_instrument":3,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":11,"phrase":"6 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/learning-graph-embeddings-for-compositional#ran","syntology_url":"https://syntology.ai/paper/2102.01987","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2102.01987"}},"official":{"repos":["ExplainableML/czsl"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/generative-multi-label-zero-shot-learning","slug":"generative-multi-label-zero-shot-learning","title":"Generative Multi-Label Zero-Shot Learning","date":"2021-01-27","arxiv_id":"2101.11606","repositories_listed":1,"syntology":null},{"url":"/paper/syntactically-guided-generative-embeddings-1","slug":"syntactically-guided-generative-embeddings-1","title":"Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action Recognition","date":"2021-01-27","arxiv_id":"2101.11530","repositories_listed":1,"syntology":null},{"url":"/paper/semantic-disentangling-generalized-zero","slug":"semantic-disentangling-generalized-zero","title":"Semantics Disentangling for Generalized Zero-Shot Learning","date":"2021-01-20","arxiv_id":"2101.07978","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/semantic-disentangling-generalized-zero#ran","syntology_url":"https://syntology.ai/paper/2101.07978","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2101.07978"}},"official":{"repos":["uqzhichen/sdgzsl"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/zero-shot-learning-by-generating-task","slug":"zero-shot-learning-by-generating-task","title":"Learning to Generate Task-Specific Adapters from Task Description","date":"2021-01-02","arxiv_id":"2101.00420","repositories_listed":1,"syntology":null},{"url":"/paper/adaptive-and-generative-zero-shot-learning","slug":"adaptive-and-generative-zero-shot-learning","title":"Adaptive and Generative Zero-Shot Learning","date":"2021-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/interaction-compass-multi-label-zero-shot","slug":"interaction-compass-multi-label-zero-shot","title":"Interaction Compass: Multi-Label Zero-Shot Learning of Human-Object Interactions via Spatial Relations","date":"2021-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/incremental-embedding-learning-via-zero-shot","slug":"incremental-embedding-learning-via-zero-shot","title":"Incremental Embedding Learning via Zero-Shot Translation","date":"2020-12-31","arxiv_id":"2012.15497","repositories_listed":1,"syntology":null},{"url":"/paper/speech-enhancement-with-zero-shot-model","slug":"speech-enhancement-with-zero-shot-model","title":"Speech Enhancement with Zero-Shot Model Selection","date":"2020-12-17","arxiv_id":"2012.09359","repositories_listed":1,"syntology":null},{"url":"/paper/learning-portrait-style-representations","slug":"learning-portrait-style-representations","title":"Learning Portrait Style Representations","date":"2020-12-08","arxiv_id":"2012.04153","repositories_listed":1,"syntology":null},{"url":"/paper/learning-disentangled-intent-representations","slug":"learning-disentangled-intent-representations","title":"Learning Class-Transductive Intent Representations for Zero-shot Intent Detection","date":"2020-12-03","arxiv_id":"2012.01721","repositories_listed":1,"syntology":null},{"url":"/paper/meta-kd-a-meta-knowledge-distillation","slug":"meta-kd-a-meta-knowledge-distillation","title":"Meta-KD: A Meta Knowledge Distillation Framework for Language Model Compression across Domains","date":"2020-12-02","arxiv_id":"2012.01266","repositories_listed":1,"syntology":null},{"url":"/paper/exploring-the-zero-shot-limit-of-fewrel","slug":"exploring-the-zero-shot-limit-of-fewrel","title":"Exploring the zero-shot limit of FewRel","date":"2020-12-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/just-ask-learning-to-answer-questions-from","slug":"just-ask-learning-to-answer-questions-from","title":"Just Ask: Learning to Answer Questions from Millions of Narrated Videos","date":"2020-12-01","arxiv_id":"2012.00451","repositories_listed":1,"syntology":null},{"url":"/paper/open-world-learning-without-labels","slug":"open-world-learning-without-labels","title":"A Review of Open-World Learning and Steps Toward Open-World Learning Without Labels","date":"2020-11-25","arxiv_id":"2011.12906","repositories_listed":1,"syntology":null},{"url":"/paper/open-vocabulary-object-detection-using","slug":"open-vocabulary-object-detection-using","title":"Open-Vocabulary Object Detection Using Captions","date":"2020-11-20","arxiv_id":"2011.10678","repositories_listed":1,"syntology":null},{"url":"/paper/a-review-of-generalized-zero-shot-learning","slug":"a-review-of-generalized-zero-shot-learning","title":"A Review of Generalized Zero-Shot Learning Methods","date":"2020-11-17","arxiv_id":"2011.08641","repositories_listed":1,"syntology":null},{"url":"/paper/zero-shot-learning-for-relation-extraction","slug":"zero-shot-learning-for-relation-extraction","title":"Zero-shot Relation Classification from Side Information","date":"2020-11-13","arxiv_id":"2011.07126","repositories_listed":1,"syntology":null},{"url":"/paper/multi-label-few-zero-shot-learning-with","slug":"multi-label-few-zero-shot-learning-with","title":"Multi-label Few/Zero-shot Learning with Knowledge Aggregated from Multiple Label Graphs","date":"2020-10-15","arxiv_id":"2010.07459","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/multi-label-few-zero-shot-learning-with#ran","syntology_url":"https://syntology.ai/paper/2010.07459","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.07459"}},"official":{"repos":["MemoriesJ/KAMG"],"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/no-rumours-please-a-multi-indic-lingual","slug":"no-rumours-please-a-multi-indic-lingual","title":"No Rumours Please! A Multi-Indic-Lingual Approach for COVID Fake-Tweet Detection","date":"2020-10-14","arxiv_id":"2010.06906","repositories_listed":1,"syntology":null},{"url":"/paper/data-agnostic-roberta-based-natural-language","slug":"data-agnostic-roberta-based-natural-language","title":"Data Agnostic RoBERTa-based Natural Language to SQL Query Generation","date":"2020-10-11","arxiv_id":"2010.05243","repositories_listed":1,"syntology":null},{"url":"/paper/causal-curiosity-rl-agents-discovering-self-1","slug":"causal-curiosity-rl-agents-discovering-self-1","title":"Causal Curiosity: RL Agents Discovering Self-supervised Experiments for Causal Representation Learning","date":"2020-10-07","arxiv_id":"2010.03110","repositories_listed":1,"syntology":null},{"url":"/paper/zest-zero-shot-learning-from-text","slug":"zest-zero-shot-learning-from-text","title":"ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization","date":"2020-10-07","arxiv_id":"2010.03276","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 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) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/zest-zero-shot-learning-from-text#ran","syntology_url":"https://syntology.ai/paper/2010.03276","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.03276"}},"official":{"repos":["tzuf/ZEST"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/an-empirical-study-on-large-scale-multi-label","slug":"an-empirical-study-on-large-scale-multi-label","title":"An Empirical Study on Large-Scale Multi-Label Text Classification Including Few and Zero-Shot Labels","date":"2020-10-04","arxiv_id":"2010.01653","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":1,"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/an-empirical-study-on-large-scale-multi-label#ran","syntology_url":"https://syntology.ai/paper/2010.01653","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2010.01653"}},"official":{"repos":["iliaschalkidis/lmtc-eurlex57k"],"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/from-pixel-to-patch-synthesize-context-aware","slug":"from-pixel-to-patch-synthesize-context-aware","title":"From Pixel to Patch: Synthesize Context-aware Features for Zero-shot Semantic Segmentation","date":"2020-09-25","arxiv_id":"2009.12232","repositories_listed":1,"syntology":null},{"url":"/paper/generalized-zero-shot-learning-via-vae","slug":"generalized-zero-shot-learning-via-vae","title":"Generalized Zero-Shot Learning via VAE-Conditioned Generative Flow","date":"2020-09-01","arxiv_id":"2009.00303","repositories_listed":1,"syntology":null},{"url":"/paper/bias-awareness-for-zero-shot-learning-the","slug":"bias-awareness-for-zero-shot-learning-the","title":"Bias-Awareness for Zero-Shot Learning the Seen and Unseen","date":"2020-08-25","arxiv_id":"2008.11185","repositories_listed":1,"syntology":null},{"url":"/paper/toward-zero-shot-unsupervised-image-to-image","slug":"toward-zero-shot-unsupervised-image-to-image","title":"Toward Zero-Shot Unsupervised Image-to-Image Translation","date":"2020-07-28","arxiv_id":"2007.14050","repositories_listed":1,"syntology":null},{"url":"/paper/towards-recognizing-unseen-categories-in","slug":"towards-recognizing-unseen-categories-in","title":"Towards Recognizing Unseen Categories in Unseen Domains","date":"2020-07-23","arxiv_id":"2007.12256","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 1 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/towards-recognizing-unseen-categories-in#ran","syntology_url":"https://syntology.ai/paper/2007.12256","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.12256"}},"official":{"repos":["mancinimassimiliano/CuMix"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/zscrgan-a-gan-based-expectation-maximization","slug":"zscrgan-a-gan-based-expectation-maximization","title":"ZSCRGAN: A GAN-based Expectation Maximization Model for Zero-Shot Retrieval of Images from Textual Descriptions","date":"2020-07-23","arxiv_id":"2007.12212","repositories_listed":1,"syntology":null},{"url":"/paper/leveraging-seen-and-unseen-semantic","slug":"leveraging-seen-and-unseen-semantic","title":"Leveraging Seen and Unseen Semantic Relationships for Generative Zero-Shot Learning","date":"2020-07-19","arxiv_id":"2007.09549","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":2,"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/leveraging-seen-and-unseen-semantic#ran","syntology_url":"https://syntology.ai/paper/2007.09549","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2007.09549"}},"official":{"repos":["Maunil/LsrGAN"],"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/invertible-zero-shot-recognition-flows","slug":"invertible-zero-shot-recognition-flows","title":"Invertible Zero-Shot Recognition Flows","date":"2020-07-09","arxiv_id":"2007.04873","repositories_listed":1,"syntology":null},{"url":"/paper/on-learning-semantic-representations-for","slug":"on-learning-semantic-representations-for","title":"On Learning Semantic Representations for Million-Scale Free-Hand Sketches","date":"2020-07-07","arxiv_id":"2007.04101","repositories_listed":1,"syntology":null},{"url":"/paper/learning-unbiased-zero-shot-semantic","slug":"learning-unbiased-zero-shot-semantic","title":"Learning unbiased zero-shot semantic segmentation networks via transductive transfer","date":"2020-07-01","arxiv_id":"2007.00515","repositories_listed":1,"syntology":null},{"url":"/paper/ontology-guided-semantic-composition-for-zero","slug":"ontology-guided-semantic-composition-for-zero","title":"Ontology-guided Semantic Composition for Zero-Shot Learning","date":"2020-06-30","arxiv_id":"2006.16917","repositories_listed":1,"syntology":null},{"url":"/paper/a-causal-view-of-compositional-zero-shot","slug":"a-causal-view-of-compositional-zero-shot","title":"A causal view of compositional zero-shot recognition","date":"2020-06-25","arxiv_id":"2006.14610","repositories_listed":1,"syntology":null}],"record_sha256":"add4b1652d16699028db794f2292434154b765324b50e3e047c0bbe2eeab4e55","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}