{"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/classification-1/papers/12","list_of":"/task/classification-1","task":"Classification","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":12,"pages_in_order":129,"rows_per_page":100,"rows":[1101,1200],"of":12815,"counts":{"archive_papers_tagged":12815,"with_a_code_link":3778,"where_syntology_ran_a_sample":582,"not_listed_spam_title":0,"listed":12815,"listed_where_code_ran":582,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":457,"every_run_a_failure_of_syntologys_instrument":125,"listed_with_a_run_with_no_instrument_failure":457,"listed_every_run_a_failure_of_syntologys_instrument":125,"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/classification-1","prev":"/task/classification-1/papers/11","next":"/task/classification-1/papers/13","papers":[{"url":"/paper/summarization-based-data-augmentation-for","slug":"summarization-based-data-augmentation-for","title":"Summarization-based Data Augmentation for Document Classification","date":"2023-12-01","arxiv_id":"2312.00513","repositories_listed":1,"syntology":null},{"url":"/paper/frc-gif-frame-ranking-based-personalized","slug":"frc-gif-frame-ranking-based-personalized","title":"FRC-GIF: Frame Ranking-based Personalized Artistic Media Generation Method for Resource Constrained Devices","date":"2023-11-30","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/gene-moe-a-sparsely-gated-framework-for-pan","slug":"gene-moe-a-sparsely-gated-framework-for-pan","title":"Gene-MOE: A sparsely gated prognosis and classification framework exploiting pan-cancer genomic information","date":"2023-11-29","arxiv_id":"2311.17401","repositories_listed":1,"syntology":null},{"url":"/paper/imputation-using-training-labels-and","slug":"imputation-using-training-labels-and","title":"Imputation using training labels and classification via label imputation","date":"2023-11-28","arxiv_id":"2311.16877","repositories_listed":1,"syntology":null},{"url":"/paper/phg-net-persistent-homology-guided-medical","slug":"phg-net-persistent-homology-guided-medical","title":"PHG-Net: Persistent Homology Guided Medical Image Classification","date":"2023-11-28","arxiv_id":"2311.17243","repositories_listed":1,"syntology":{"n":9,"n_ran":4,"n_constructed":0,"n_ran_checked":4,"n_instrument":0,"n_unverified":5,"n_honours":2,"n_violates":1,"n_no_contract":1,"n_pointer_only":9,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 2 honoured, 1 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/phg-net-persistent-homology-guided-medical#ran","syntology_url":"https://syntology.ai/paper/2311.17243","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.17243"}},"official":{"repos":["yaoppeng/topoclassification"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/scalable-label-distribution-learning-for","slug":"scalable-label-distribution-learning-for","title":"Scalable Label Distribution Learning for Multi-Label Classification","date":"2023-11-28","arxiv_id":"2311.16556","repositories_listed":1,"syntology":null},{"url":"/paper/text2tree-aligning-text-representation-to-the","slug":"text2tree-aligning-text-representation-to-the","title":"Text2Tree: Aligning Text Representation to the Label Tree Hierarchy for Imbalanced Medical Classification","date":"2023-11-28","arxiv_id":"2311.16650","repositories_listed":1,"syntology":null},{"url":"/paper/bert-goes-off-topic-investigating-the-domain","slug":"bert-goes-off-topic-investigating-the-domain","title":"BERT Goes Off-Topic: Investigating the Domain Transfer Challenge using Genre Classification","date":"2023-11-27","arxiv_id":"2311.16083","repositories_listed":1,"syntology":null},{"url":"/paper/peptide-binding-classification-on-quantum","slug":"peptide-binding-classification-on-quantum","title":"Peptide Binding Classification on Quantum Computers","date":"2023-11-27","arxiv_id":"2311.15696","repositories_listed":1,"syntology":null},{"url":"/paper/sparsify-then-classify-from-internal-neurons","slug":"sparsify-then-classify-from-internal-neurons","title":"SPIN: Sparsifying and Integrating Internal Neurons in Large Language Models for Text Classification","date":"2023-11-27","arxiv_id":"2311.15983","repositories_listed":1,"syntology":null},{"url":"/paper/hyperdid-hyperspectral-intrinsic-image","slug":"hyperdid-hyperspectral-intrinsic-image","title":"HyperDID: Hyperspectral Intrinsic Image Decomposition with Deep Feature Embedding","date":"2023-11-25","arxiv_id":"2311.14899","repositories_listed":1,"syntology":null},{"url":"/paper/hardware-resilience-properties-of-text-guided-1","slug":"hardware-resilience-properties-of-text-guided-1","title":"Hardware Resilience Properties of Text-Guided Image Classifiers","date":"2023-11-23","arxiv_id":"2311.14062","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"phrase":"3 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; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/hardware-resilience-properties-of-text-guided-1#ran","syntology_url":"https://syntology.ai/paper/2311.14062","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.14062"}},"official":{"repos":["talalwasim/textguidedresilience"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/hard-label-black-box-node-injection-attack-on","slug":"hard-label-black-box-node-injection-attack-on","title":"Hard Label Black Box Node Injection Attack on Graph Neural Networks","date":"2023-11-22","arxiv_id":"2311.13244","repositories_listed":1,"syntology":null},{"url":"/paper/spanning-training-progress-temporal-dual","slug":"spanning-training-progress-temporal-dual","title":"Spanning Training Progress: Temporal Dual-Depth Scoring (TDDS) for Enhanced Dataset Pruning","date":"2023-11-22","arxiv_id":"2311.13613","repositories_listed":1,"syntology":{"n":11,"n_ran":6,"n_constructed":0,"n_ran_checked":4,"n_instrument":2,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":1,"phrase":"6 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; 2 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/spanning-training-progress-temporal-dual#ran","syntology_url":"https://syntology.ai/paper/2311.13613","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.13613"}},"official":{"repos":["zhangxin-xd/Dataset-Pruning-TDDS"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/unified-classification-and-rejection-a-one","slug":"unified-classification-and-rejection-a-one","title":"Unified Classification and Rejection: A One-versus-All Framework","date":"2023-11-22","arxiv_id":"2311.13355","repositories_listed":1,"syntology":{"n":4,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":4,"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) · 2 unverified","sample_list":"/paper/unified-classification-and-rejection-a-one#ran","syntology_url":"https://syntology.ai/paper/2311.13355","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.13355"}},"official":{"repos":["zhen-cheng121/cpn_ova_unified"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["unlocated"]}}},{"url":"/paper/fair-text-classification-with-wasserstein","slug":"fair-text-classification-with-wasserstein","title":"Fair Text Classification with Wasserstein Independence","date":"2023-11-21","arxiv_id":"2311.12689","repositories_listed":1,"syntology":null},{"url":"/paper/high-resolution-image-based-malware","slug":"high-resolution-image-based-malware","title":"High-resolution Image-based Malware Classification using Multiple Instance Learning","date":"2023-11-21","arxiv_id":"2311.12760","repositories_listed":1,"syntology":null},{"url":"/paper/random-linear-projections-loss-for-hyperplane","slug":"random-linear-projections-loss-for-hyperplane","title":"Random Linear Projections Loss for Hyperplane-Based Optimization in Neural Networks","date":"2023-11-21","arxiv_id":"2311.12356","repositories_listed":1,"syntology":null},{"url":"/paper/rethinking-the-output-architecture-for-sound","slug":"rethinking-the-output-architecture-for-sound","title":"Eliminating Quantization Errors in Classification-Based Sound Source Localization","date":"2023-11-21","arxiv_id":"2311.12305","repositories_listed":1,"syntology":null},{"url":"/paper/llms-as-visual-explainers-advancing-image","slug":"llms-as-visual-explainers-advancing-image","title":"LLMs as Visual Explainers: Advancing Image Classification with Evolving Visual Descriptions","date":"2023-11-20","arxiv_id":"2311.11904","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"3 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; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/llms-as-visual-explainers-advancing-image#ran","syntology_url":"https://syntology.ai/paper/2311.11904","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.11904"}},"official":{"repos":["zhuole1025/llms_as_visual_explainers"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/multi-task-faces-mtf-data-set-a-legally-and","slug":"multi-task-faces-mtf-data-set-a-legally-and","title":"Multi-Task Faces (MTF) Data Set: A Legally and Ethically Compliant Collection of Face Images for Various Classification Tasks","date":"2023-11-20","arxiv_id":"2311.11882","repositories_listed":1,"syntology":null},{"url":"/paper/node-classification-in-random-trees","slug":"node-classification-in-random-trees","title":"Node Classification in Random Trees","date":"2023-11-20","arxiv_id":"2311.12167","repositories_listed":1,"syntology":null},{"url":"/paper/which-ai-technique-is-better-to-classify","slug":"which-ai-technique-is-better-to-classify","title":"Which AI Technique Is Better to Classify Requirements? An Experiment with SVM, LSTM, and ChatGPT","date":"2023-11-20","arxiv_id":"2311.11547","repositories_listed":1,"syntology":null},{"url":"/paper/evidential-uncertainty-quantification-a","slug":"evidential-uncertainty-quantification-a","title":"Evidential Uncertainty Quantification: A Variance-Based Perspective","date":"2023-11-19","arxiv_id":"2311.11367","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":5,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/evidential-uncertainty-quantification-a#ran","syntology_url":"https://syntology.ai/paper/2311.11367","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.11367"}},"official":{"repos":["kerrydrx/evidentialada"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/optimal-locally-private-nonparametric","slug":"optimal-locally-private-nonparametric","title":"Optimal Locally Private Nonparametric Classification with Public Data","date":"2023-11-19","arxiv_id":"2311.11369","repositories_listed":1,"syntology":null},{"url":"/paper/textguard-provable-defense-against-backdoor","slug":"textguard-provable-defense-against-backdoor","title":"TextGuard: Provable Defense against Backdoor Attacks on Text Classification","date":"2023-11-19","arxiv_id":"2311.11225","repositories_listed":1,"syntology":{"n":11,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":11,"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) · 5 unverified","sample_list":"/paper/textguard-provable-defense-against-backdoor#ran","syntology_url":"https://syntology.ai/paper/2311.11225","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.11225"}},"official":{"repos":["ai-secure/textguard"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/representing-visual-classification-as-a","slug":"representing-visual-classification-as-a","title":"Representing visual classification as a linear combination of words","date":"2023-11-18","arxiv_id":"2311.10933","repositories_listed":1,"syntology":null},{"url":"/paper/closely-spaced-object-classification-using","slug":"closely-spaced-object-classification-using","title":"Closely-Spaced Object Classification Using MuyGPyS","date":"2023-11-17","arxiv_id":"2311.10904","repositories_listed":1,"syntology":null},{"url":"/paper/senetv2-aggregated-dense-layer-for","slug":"senetv2-aggregated-dense-layer-for","title":"SENetV2: Aggregated dense layer for channelwise and global representations","date":"2023-11-17","arxiv_id":"2311.10807","repositories_listed":1,"syntology":null},{"url":"/paper/capturing-perspectives-of-crowdsourced","slug":"capturing-perspectives-of-crowdsourced","title":"Capturing Perspectives of Crowdsourced Annotators in Subjective Learning Tasks","date":"2023-11-16","arxiv_id":"2311.09743","repositories_listed":1,"syntology":null},{"url":"/paper/formal-verification-of-long-short-term-memory","slug":"formal-verification-of-long-short-term-memory","title":"Formal Verification of Long Short-Term Memory based Audio Classifiers: A Star based Approach","date":"2023-11-16","arxiv_id":"2311.12130","repositories_listed":1,"syntology":null},{"url":"/paper/multi-view-spectrogram-transformer-for","slug":"multi-view-spectrogram-transformer-for","title":"Multi-View Spectrogram Transformer for Respiratory Sound Classification","date":"2023-11-16","arxiv_id":"2311.09655","repositories_listed":1,"syntology":null},{"url":"/paper/convnet-vs-transformer-supervised-vs-clip","slug":"convnet-vs-transformer-supervised-vs-clip","title":"ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy","date":"2023-11-15","arxiv_id":"2311.09215","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/convnet-vs-transformer-supervised-vs-clip#ran","syntology_url":"https://syntology.ai/paper/2311.09215","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.09215"}},"official":{"repos":["kirill-vish/beyond-inet"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/token-prediction-as-implicit-classification","slug":"token-prediction-as-implicit-classification","title":"Token Prediction as Implicit Classification to Identify LLM-Generated Text","date":"2023-11-15","arxiv_id":"2311.08723","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":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) · 3 unverified","sample_list":"/paper/token-prediction-as-implicit-classification#ran","syntology_url":"https://syntology.ai/paper/2311.08723","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2311.08723"}},"official":{"repos":["markchenyutian/t5-sentinel-public"],"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/towards-label-embedding-measuring","slug":"towards-label-embedding-measuring","title":"Human-in-the-loop: Towards Label Embeddings for Measuring Classification Difficulty","date":"2023-11-15","arxiv_id":"2311.08874","repositories_listed":1,"syntology":null},{"url":"/paper/the-hyperdimensional-transform-for","slug":"the-hyperdimensional-transform-for","title":"The Hyperdimensional Transform for Distributional Modelling, Regression and Classification","date":"2023-11-14","arxiv_id":"2311.08150","repositories_listed":1,"syntology":null},{"url":"/paper/understanding-learning-from-eeg-data","slug":"understanding-learning-from-eeg-data","title":"Understanding learning from EEG data: Combining machine learning and feature engineering based on hidden Markov models and mixed models","date":"2023-11-14","arxiv_id":"2311.08113","repositories_listed":1,"syntology":null},{"url":"/paper/a-voting-approach-for-explainable","slug":"a-voting-approach-for-explainable","title":"A Voting Approach for Explainable Classification with Rule Learning","date":"2023-11-13","arxiv_id":"2311.07323","repositories_listed":1,"syntology":null},{"url":"/paper/automated-classification-of-model-errors-on-1","slug":"automated-classification-of-model-errors-on-1","title":"Automated Classification of Model Errors on ImageNet","date":"2023-11-13","arxiv_id":"2401.02430","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":0,"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/automated-classification-of-model-errors-on-1#ran","syntology_url":"https://syntology.ai/paper/2401.02430","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.02430"}},"official":{"repos":["eth-sri/automated-error-analysis"],"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/connecting-the-dots-graph-neural-network","slug":"connecting-the-dots-graph-neural-network","title":"Connecting the Dots: Graph Neural Network Powered Ensemble and Classification of Medical Images","date":"2023-11-13","arxiv_id":"2311.07321","repositories_listed":1,"syntology":null},{"url":"/paper/robust-text-classification-analyzing","slug":"robust-text-classification-analyzing","title":"Robust Text Classification: Analyzing Prototype-Based Networks","date":"2023-11-11","arxiv_id":"2311.06647","repositories_listed":1,"syntology":null},{"url":"/paper/eeg-dg-a-multi-source-domain-generalization","slug":"eeg-dg-a-multi-source-domain-generalization","title":"EEG-DG: A Multi-Source Domain Generalization Framework for Motor Imagery EEG Classification","date":"2023-11-09","arxiv_id":"2311.05415","repositories_listed":1,"syntology":null},{"url":"/paper/auto-deep-learning-for-bioacoustic-signals","slug":"auto-deep-learning-for-bioacoustic-signals","title":"Auto deep learning for bioacoustic signals","date":"2023-11-08","arxiv_id":"2311.04945","repositories_listed":1,"syntology":null},{"url":"/paper/predicting-properties-of-nodes-via-community","slug":"predicting-properties-of-nodes-via-community","title":"Predicting Properties of Nodes via Community-Aware Features","date":"2023-11-08","arxiv_id":"2311.04730","repositories_listed":1,"syntology":null},{"url":"/paper/dual-stream-attention-transformers-for-sewer","slug":"dual-stream-attention-transformers-for-sewer","title":"Dual-Stream Attention Transformers for Sewer Defect Classification","date":"2023-11-07","arxiv_id":"2311.16145","repositories_listed":1,"syntology":null},{"url":"/paper/cross-level-distillation-and-feature","slug":"cross-level-distillation-and-feature","title":"Cross-Level Distillation and Feature Denoising for Cross-Domain Few-Shot Classification","date":"2023-11-04","arxiv_id":"2311.02392","repositories_listed":1,"syntology":null},{"url":"/paper/a-new-korean-text-classification-benchmark","slug":"a-new-korean-text-classification-benchmark","title":"A New Korean Text Classification Benchmark for Recognizing the Political Intents in Online Newspapers","date":"2023-11-03","arxiv_id":"2311.01712","repositories_listed":1,"syntology":null},{"url":"/paper/generating-unbiased-pseudo-labels-via-a","slug":"generating-unbiased-pseudo-labels-via-a","title":"Generating Unbiased Pseudo-labels via a Theoretically Guaranteed Chebyshev Constraint to Unify Semi-supervised Classification and Regression","date":"2023-11-03","arxiv_id":"2311.01782","repositories_listed":1,"syntology":null},{"url":"/paper/towards-machine-unlearning-benchmarks","slug":"towards-machine-unlearning-benchmarks","title":"Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition Systems","date":"2023-11-03","arxiv_id":"2311.02240","repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-multimodal-information-bottleneck-for","slug":"dynamic-multimodal-information-bottleneck-for","title":"Dynamic Multimodal Information Bottleneck for Multimodality Classification","date":"2023-11-02","arxiv_id":"2311.01066","repositories_listed":1,"syntology":null},{"url":"/paper/multi-view-relation-learning-for-cross-domain","slug":"multi-view-relation-learning-for-cross-domain","title":"Multi-level Relation Learning for Cross-domain Few-shot Hyperspectral Image Classification","date":"2023-11-02","arxiv_id":"2311.01212","repositories_listed":1,"syntology":null},{"url":"/paper/adasent-efficient-domain-adapted-sentence","slug":"adasent-efficient-domain-adapted-sentence","title":"AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification","date":"2023-11-01","arxiv_id":"2311.00408","repositories_listed":1,"syntology":null},{"url":"/paper/re-scoring-using-image-language-similarity","slug":"re-scoring-using-image-language-similarity","title":"Re-Scoring Using Image-Language Similarity for Few-Shot Object Detection","date":"2023-11-01","arxiv_id":"2311.00278","repositories_listed":1,"syntology":null},{"url":"/paper/datazoo-streamlining-traffic-classification","slug":"datazoo-streamlining-traffic-classification","title":"DataZoo: Streamlining Traffic Classification Experiments","date":"2023-10-30","arxiv_id":"2310.19568","repositories_listed":1,"syntology":null},{"url":"/paper/generalizing-to-unseen-domains-in-diabetic","slug":"generalizing-to-unseen-domains-in-diabetic","title":"Generalizing to Unseen Domains in Diabetic Retinopathy Classification","date":"2023-10-26","arxiv_id":"2310.17255","repositories_listed":1,"syntology":null},{"url":"/paper/motionagformer-enhancing-3d-human-pose","slug":"motionagformer-enhancing-3d-human-pose","title":"MotionAGFormer: Enhancing 3D Human Pose Estimation with a Transformer-GCNFormer Network","date":"2023-10-25","arxiv_id":"2310.16288","repositories_listed":1,"syntology":{"n":16,"n_ran":14,"n_constructed":0,"n_ran_checked":13,"n_instrument":1,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":13,"n_pointer_only":3,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/motionagformer-enhancing-3d-human-pose#ran","syntology_url":"https://syntology.ai/paper/2310.16288","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.16288"}},"official":{"repos":["taatiteam/motionagformer"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":13,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/learning-interpretable-rules-for-scalable","slug":"learning-interpretable-rules-for-scalable","title":"Learning Interpretable Rules for Scalable Data Representation and Classification","date":"2023-10-22","arxiv_id":"2310.14336","repositories_listed":1,"syntology":{"n":15,"n_ran":10,"n_constructed":9,"n_ran_checked":10,"n_instrument":0,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":10,"n_pointer_only":0,"phrase":"10 ran (of which 9 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/learning-interpretable-rules-for-scalable#ran","syntology_url":"https://syntology.ai/paper/2310.14336","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.14336"}},"official":{"repos":["12wang3/rrl"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":9,"n_ran_no_instrument_failure":10,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/prompt-based-grouping-transformer-for-nucleus","slug":"prompt-based-grouping-transformer-for-nucleus","title":"Prompt-based Grouping Transformer for Nucleus Detection and Classification","date":"2023-10-22","arxiv_id":"2310.14176","repositories_listed":1,"syntology":null},{"url":"/paper/finentity-entity-level-sentiment","slug":"finentity-entity-level-sentiment","title":"FinEntity: Entity-level Sentiment Classification for Financial Texts","date":"2023-10-19","arxiv_id":"2310.12406","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":5,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/finentity-entity-level-sentiment#ran","syntology_url":"https://syntology.ai/paper/2310.12406","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.12406"}},"official":{"repos":["yixuantt/finentity"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/transformer-based-entity-legal-form","slug":"transformer-based-entity-legal-form","title":"Transformer-based Entity Legal Form Classification","date":"2023-10-19","arxiv_id":"2310.12766","repositories_listed":1,"syntology":null},{"url":"/paper/analyze-mass-spectrometry-data-with","slug":"analyze-mass-spectrometry-data-with","title":"Analyze Mass Spectrometry data with Artificial Intelligence to assist the understanding of past habitability of Mars and provide insights for future missions","date":"2023-10-18","arxiv_id":"2310.11888","repositories_listed":1,"syntology":null},{"url":"/paper/banglaabusememe-a-dataset-for-bengali-abusive","slug":"banglaabusememe-a-dataset-for-bengali-abusive","title":"BanglaAbuseMeme: A Dataset for Bengali Abusive Meme Classification","date":"2023-10-18","arxiv_id":"2310.11748","repositories_listed":1,"syntology":null},{"url":"/paper/efficacy-of-dual-encoders-for-extreme-multi","slug":"efficacy-of-dual-encoders-for-extreme-multi","title":"Dual-Encoders for Extreme Multi-Label Classification","date":"2023-10-16","arxiv_id":"2310.10636","repositories_listed":1,"syntology":null},{"url":"/paper/impact-of-data-synthesis-strategies-for-the","slug":"impact-of-data-synthesis-strategies-for-the","title":"Impact of Data Synthesis Strategies for the Classification of Craniosynostosis","date":"2023-10-16","arxiv_id":"2310.10199","repositories_listed":1,"syntology":null},{"url":"/paper/probabilistic-classification-by-density","slug":"probabilistic-classification-by-density","title":"Probabilistic Classification by Density Estimation Using Gaussian Mixture Model and Masked Autoregressive Flow","date":"2023-10-16","arxiv_id":"2310.10843","repositories_listed":1,"syntology":null},{"url":"/paper/new-benchmarks-for-asian-facial-recognition","slug":"new-benchmarks-for-asian-facial-recognition","title":"New Benchmarks for Asian Facial Recognition Tasks: Face Classification with Large Foundation Models","date":"2023-10-15","arxiv_id":"2310.09756","repositories_listed":1,"syntology":null},{"url":"/paper/overview-of-imagearg-2023-the-first-shared","slug":"overview-of-imagearg-2023-the-first-shared","title":"Overview of ImageArg-2023: The First Shared Task in Multimodal Argument Mining","date":"2023-10-15","arxiv_id":"2310.12172","repositories_listed":1,"syntology":null},{"url":"/paper/causality-and-independence-enhancement-for","slug":"causality-and-independence-enhancement-for","title":"Causality and Independence Enhancement for Biased Node Classification","date":"2023-10-14","arxiv_id":"2310.09586","repositories_listed":1,"syntology":null},{"url":"/paper/mirage-model-agnostic-graph-distillation-for","slug":"mirage-model-agnostic-graph-distillation-for","title":"Mirage: Model-Agnostic Graph Distillation for Graph Classification","date":"2023-10-14","arxiv_id":"2310.09486","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":1,"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; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/mirage-model-agnostic-graph-distillation-for#ran","syntology_url":"https://syntology.ai/paper/2310.09486","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.09486"}},"official":{"repos":["idea-iitd/mirage"],"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/baitbuster-bangla-a-comprehensive-dataset-for","slug":"baitbuster-bangla-a-comprehensive-dataset-for","title":"BaitBuster-Bangla: A Comprehensive Dataset for Clickbait Detection in Bangla with Multi-Feature and Multi-Modal Analysis","date":"2023-10-13","arxiv_id":"2310.11465","repositories_listed":1,"syntology":null},{"url":"/paper/long-tailed-classification-based-on-coarse","slug":"long-tailed-classification-based-on-coarse","title":"Long-Tailed Classification Based on Coarse-Grained Leading Forest and Multi-Center Loss","date":"2023-10-12","arxiv_id":"2310.08206","repositories_listed":1,"syntology":null},{"url":"/paper/infocl-alleviating-catastrophic-forgetting-in","slug":"infocl-alleviating-catastrophic-forgetting-in","title":"InfoCL: Alleviating Catastrophic Forgetting in Continual Text Classification from An Information Theoretic Perspective","date":"2023-10-10","arxiv_id":"2310.06362","repositories_listed":1,"syntology":null},{"url":"/paper/a-critical-look-at-classic-test-time","slug":"a-critical-look-at-classic-test-time","title":"From Question to Exploration: Test-Time Adaptation in Semantic Segmentation?","date":"2023-10-09","arxiv_id":"2310.05341","repositories_listed":1,"syntology":null},{"url":"/paper/xal-explainable-active-learning-makes","slug":"xal-explainable-active-learning-makes","title":"XAL: EXplainable Active Learning Makes Classifiers Better Low-resource Learners","date":"2023-10-09","arxiv_id":"2310.05502","repositories_listed":1,"syntology":null},{"url":"/paper/robust-gbdt-a-novel-gradient-boosting-model","slug":"robust-gbdt-a-novel-gradient-boosting-model","title":"Robust-GBDT: GBDT with Nonconvex Loss for Tabular Classification in the Presence of Label Noise and Class Imbalance","date":"2023-10-08","arxiv_id":"2310.05067","repositories_listed":1,"syntology":null},{"url":"/paper/luminet-the-bright-side-of-perceptual","slug":"luminet-the-bright-side-of-perceptual","title":"LumiNet: The Bright Side of Perceptual Knowledge Distillation","date":"2023-10-05","arxiv_id":"2310.03669","repositories_listed":1,"syntology":null},{"url":"/paper/ajwa-or-medjool-a-binary-balanced-dataset-to","slug":"ajwa-or-medjool-a-binary-balanced-dataset-to","title":"Ajwa or Medjool: a binary balanced dataset to teach machine learning عجوة أو مجدول: مجموعة بيانات متوازنة الصنفين لتدريس تعلم الآلة‏","date":"2023-09-30","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/feedback-guided-data-synthesis-for-imbalanced","slug":"feedback-guided-data-synthesis-for-imbalanced","title":"Feedback-guided Data Synthesis for Imbalanced Classification","date":"2023-09-29","arxiv_id":"2310.00158","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":4,"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) · 3 unverified","sample_list":"/paper/feedback-guided-data-synthesis-for-imbalanced#ran","syntology_url":"https://syntology.ai/paper/2310.00158","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2310.00158"}},"official":{"repos":["facebookresearch/feedback-guided-data-synthesis"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/logarithm-transform-aided-gaussian-sampling","slug":"logarithm-transform-aided-gaussian-sampling","title":"Logarithm-transform aided Gaussian Sampling for Few-Shot Learning","date":"2023-09-28","arxiv_id":"2309.16337","repositories_listed":1,"syntology":null},{"url":"/paper/ultra-low-power-image-classification-on","slug":"ultra-low-power-image-classification-on","title":"Ultra-low-power Image Classification on Neuromorphic Hardware","date":"2023-09-28","arxiv_id":"2309.16795","repositories_listed":1,"syntology":null},{"url":"/paper/boosting-high-resolution-image-classification","slug":"boosting-high-resolution-image-classification","title":"Boosting High Resolution Image Classification with Scaling-up Transformers","date":"2023-09-26","arxiv_id":"2309.15277","repositories_listed":1,"syntology":null},{"url":"/paper/weakly-supervised-semantic-segmentation-by-4","slug":"weakly-supervised-semantic-segmentation-by-4","title":"Weakly Supervised Semantic Segmentation by Knowledge Graph Inference","date":"2023-09-25","arxiv_id":"2309.14057","repositories_listed":1,"syntology":null},{"url":"/paper/multiple-relations-classification-using","slug":"multiple-relations-classification-using","title":"Multiple Relations Classification using Imbalanced Predictions Adaptation","date":"2023-09-24","arxiv_id":"2309.13718","repositories_listed":1,"syntology":null},{"url":"/paper/use-of-large-language-models-for-stance","slug":"use-of-large-language-models-for-stance","title":"Prompting and Fine-Tuning Open-Sourced Large Language Models for Stance Classification","date":"2023-09-24","arxiv_id":"2309.13734","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/use-of-large-language-models-for-stance#ran","syntology_url":"https://syntology.ai/paper/2309.13734","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.13734"}},"official":{"repos":["ijcruic/llm-stance-labeling"],"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/being-aware-of-localization-accuracy-by","slug":"being-aware-of-localization-accuracy-by","title":"Being Aware of Localization Accuracy By Generating Predicted-IoU-Guided Quality Scores","date":"2023-09-23","arxiv_id":"2309.13269","repositories_listed":1,"syntology":null},{"url":"/paper/accelerating-thematic-investment-with-prompt","slug":"accelerating-thematic-investment-with-prompt","title":"Prompt Tuned Embedding Classification for Multi-Label Industry Sector Allocation","date":"2023-09-21","arxiv_id":"2309.12075","repositories_listed":1,"syntology":null},{"url":"/paper/improving-article-classification-with-edge","slug":"improving-article-classification-with-edge","title":"Article Classification with Graph Neural Networks and Multigraphs","date":"2023-09-20","arxiv_id":"2309.11341","repositories_listed":1,"syntology":null},{"url":"/paper/multi-label-takagi-sugeno-kang-fuzzy-system","slug":"multi-label-takagi-sugeno-kang-fuzzy-system","title":"Multi-Label Takagi-Sugeno-Kang Fuzzy System","date":"2023-09-20","arxiv_id":"2309.11469","repositories_listed":1,"syntology":null},{"url":"/paper/amurd-annotated-multilingual-receipts-dataset","slug":"amurd-annotated-multilingual-receipts-dataset","title":"AMuRD: Annotated Arabic-English Receipt Dataset for Key Information Extraction and Classification","date":"2023-09-18","arxiv_id":"2309.09800","repositories_listed":1,"syntology":null},{"url":"/paper/detecting-covariate-drift-in-text-data-using","slug":"detecting-covariate-drift-in-text-data-using","title":"Detecting covariate drift in text data using document embeddings and dimensionality reduction","date":"2023-09-17","arxiv_id":"2309.10000","repositories_listed":1,"syntology":null},{"url":"/paper/large-language-models-for-failure-mode","slug":"large-language-models-for-failure-mode","title":"Large Language Models for Failure Mode Classification: An Investigation","date":"2023-09-15","arxiv_id":"2309.08181","repositories_listed":1,"syntology":null},{"url":"/paper/temporal-aware-hierarchical-mask","slug":"temporal-aware-hierarchical-mask","title":"Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentation","date":"2023-09-14","arxiv_id":"2309.08020","repositories_listed":1,"syntology":null},{"url":"/paper/graph-contextual-contrasting-for-multivariate","slug":"graph-contextual-contrasting-for-multivariate","title":"Graph-Aware Contrasting for Multivariate Time-Series Classification","date":"2023-09-11","arxiv_id":"2309.05202","repositories_listed":1,"syntology":null},{"url":"/paper/adaptive-conformal-classification-with-noisy","slug":"adaptive-conformal-classification-with-noisy","title":"Adaptive conformal classification with noisy labels","date":"2023-09-10","arxiv_id":"2309.05092","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":0,"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/adaptive-conformal-classification-with-noisy#ran","syntology_url":"https://syntology.ai/paper/2309.05092","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2309.05092"}},"official":{"repos":["msesia/conformal-label-noise"],"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/multi-modal-extreme-classification-1","slug":"multi-modal-extreme-classification-1","title":"Multi-modal Extreme Classification","date":"2023-09-10","arxiv_id":"2309.04961","repositories_listed":1,"syntology":null},{"url":"/paper/audrandaug-random-image-augmentations-for","slug":"audrandaug-random-image-augmentations-for","title":"AudRandAug: Random Image Augmentations for Audio Classification","date":"2023-09-09","arxiv_id":"2309.04762","repositories_listed":1,"syntology":null},{"url":"/paper/dataset-generation-and-bonobo-classification","slug":"dataset-generation-and-bonobo-classification","title":"Dataset Generation and Bonobo Classification from Weakly Labelled Videos","date":"2023-09-07","arxiv_id":"2309.03671","repositories_listed":1,"syntology":null},{"url":"/paper/filtration-surfaces-for-dynamic-graph","slug":"filtration-surfaces-for-dynamic-graph","title":"Filtration Surfaces for Dynamic Graph Classification","date":"2023-09-07","arxiv_id":"2309.03616","repositories_listed":1,"syntology":null},{"url":"/paper/text-to-feature-diffusion-for-audio-visual","slug":"text-to-feature-diffusion-for-audio-visual","title":"Text-to-feature diffusion for audio-visual few-shot learning","date":"2023-09-07","arxiv_id":"2309.03869","repositories_listed":1,"syntology":null},{"url":"/paper/usa-universal-sentiment-analysis-model","slug":"usa-universal-sentiment-analysis-model","title":"USA: Universal Sentiment Analysis Model & Construction of Japanese Sentiment Text Classification and Part of Speech Dataset","date":"2023-09-07","arxiv_id":"2309.03787","repositories_listed":1,"syntology":null}],"record_sha256":"7af18d9aa598e656be9fa7a9694cac8e5840b4f8080ef7e65a9bcd10b7552f44","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}