Missing Labels

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Most implemented papers archive 2025-07-28

30 shown of 50 papers with code (139 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Generalized test utilities for long-tail performance in extreme multi-label classification
  9 Nov 2023 2 repositories listed Syntology ran 17 of 40 samples · 23 unverified
  As such, it is characterized by long-tail labels, i.
• Cross-Prediction-Powered Inference
  28 Sep 2023 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  We show that cross-prediction is consistently more powerful than an adaptation of prediction-powered inference in which a fraction of the labeled data is split off and used to train the model.
• DICNet: Deep Instance-Level Contrastive Network for Double Incomplete Multi-View Multi-Label Classification
  15 Mar 2023 2 repositories listed Syntology ran 2 of 7 samples · 5 unverified
  To deal with the double incomplete multi-view multi-label classification problem, we propose a deep instance-level contrastive network, namely DICNet.
• The Dice loss in the context of missing or empty labels: Introducing Φ and ε
  19 Jul 2022 2 repositories listed
  We find and propose heuristic combinations of Φ and ϵ that work in a segmentation setting with either missing or empty labels.
• Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
  13 Dec 2021 2 repositories listed Syntology ran 2 of 7 samples · 5 unverified
  Multi-label learning in the presence of missing labels (MLML) is a challenging problem.
• Label-set Loss Functions for Partial Supervision: Application to Fetal Brain 3D MRI Parcellation
  8 Jul 2021 2 repositories listed
  Deep neural networks have increased the accuracy of automatic segmentation, however, their accuracy depends on the availability of a large number of fully segmented images.
• Multi-Label Learning from Single Positive Labels
  17 Jun 2021 2 repositories listed Syntology ran 3 of 13 samples · 10 unverified
  When the number of potential labels is large, human annotators find it difficult to mention all applicable labels for each training image.
• Semi-Supervised Online Structure Learning for Composite Event Recognition
  1 Mar 2018 2 repositories listed
  Online structure learning approaches, such as those stemming from Statistical Relational Learning, enable the discovery of complex relations in noisy data streams.
• Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning
  26 May 2025 1 repository listed
  It not only enables models to simultaneously address catastrophic forgetting, missing labels, and class imbalance challenges, but also serves as an orthogonal solution that seamlessly integrates with existing approaches.
• Conformal Prediction with Corrupted Labels: Uncertain Imputation and Robust Re-weighting
  7 May 2025 1 repository listed
  The validity of conformal prediction, however, holds under the i.
• On the Necessity of World Knowledge for Mitigating Missing Labels in Extreme Classification
  18 Aug 2024 1 repository listed
  Extreme Classification (XC) aims to map a query to the most relevant documents from a very large document set.
• Text-Region Matching for Multi-Label Image Recognition with Missing Labels
  26 Jul 2024 1 repository listed
  Compared to existing methods, we advocate exploring the information of category-aware regions rather than the entire image or pixels, which contributes to bridging the semantic gap between textual and visual…
• Improving Audio Spectrogram Transformers for Sound Event Detection Through Multi-Stage Training
  17 Jul 2024 1 repository listed Syntology ran 5 of 5 samples · 0 unverified · 5 pointer-only (licence)
  We fine-tune three large Audio Spectrogram Transformers, PaSST, BEATs, and ATST, on the joint DESED and MAESTRO datasets in a two-stage training procedure.
• FedMLP: Federated Multi-Label Medical Image Classification under Task Heterogeneity
  27 Jun 2024 1 repository listed
  Experiments on two publicly-available medical datasets validate the superiority of FedMLP against the state-of-the-art both federated semi-supervised and noisy label learning approaches under task heterogeneity.
• A SMART Mnemonic Sounds like "Glue Tonic": Mixing LLMs with Student Feedback to Make Mnemonic Learning Stick
  21 Jun 2024 1 repository listed
  To train SMART, we first fine-tune LLaMA-2 on a curated set of user-written mnemonics.
• Boosting Single Positive Multi-label Classification with Generalized Robust Loss
  6 May 2024 1 repository listed Syntology ran 4 of 4 samples · 0 unverified · 4 pointer-only (licence)
  Multi-label learning (MLL) requires comprehensive multi-semantic annotations that is hard to fully obtain, thus often resulting in missing labels scenarios.
• SeSaMe: A Framework to Simulate Self-Reported Ground Truth for Mental Health Sensing Studies
  25 Mar 2024 1 repository listed
  In this work, we introduce the Scale Scores Simulation using Mental Models (SeSaMe) framework to alleviate participants' burden in digital mental health studies.
• Online Semi-Supervised Learning of Composite Event Rules by Combining Structure and Mass-Based Predicate Similarity
  15 Dec 2023 1 repository listed
  Additionally, the enhanced SPLICE method, improves the graph construction process, by storing a synopsis of the past, in order to achieve more informed labelling on the local graphs.
• Imputation using training labels and classification via label imputation
  28 Nov 2023 1 repository listed
  We propose Classification Based on MissForest Imputation (CBMI), a classification strategy that initializes the predicted test label with missing values and stacks the label with the input for imputation, allowing the…
• netFound: Foundation Model for Network Security
  25 Oct 2023 1 repository listed
  This lack of progress can be attributed to an overreliance on supervised learning techniques and the associated challenges of curating well-specified labeled training data.
• Balancing Efficiency vs. Effectiveness and Providing Missing Label Robustness in Multi-Label Stream Classification
  1 Oct 2023 1 repository listed
  Our results demonstrate that the proposed approach ML-BELS is successful in balancing effectiveness and efficiency, and is robust to missing labels and concept drift.
• Auxiliary Label Embedding for Multi-label Learning with Missing Labels
  6 May 2023 1 repository listed
  Label correlation has been exploited for multi-label learning in different ways.
• Synthetic Data-based Detection of Zebras in Drone Imagery
  30 Apr 2023 1 repository listed
  Through extensive evaluations of our model with real-world data from i) limited datasets available on the internet and ii) a new one collected and manually labelled by us, we show that we can detect zebras by using only…
• Scale Federated Learning for Label Set Mismatch in Medical Image Classification
  14 Apr 2023 1 repository listed
  Federated learning (FL) has been introduced to the healthcare domain as a decentralized learning paradigm that allows multiple parties to train a model collaboratively without privacy leakage.
• Deep Double Incomplete Multi-view Multi-label Learning with Incomplete Labels and Missing Views
  23 Mar 2023 1 repository listed
  View missing and label missing are two challenging problems in the applications of multi-view multi-label classification scenery.
• Recall, Robustness, and Lexicographic Evaluation
  22 Feb 2023 1 repository listed
  In light of this debate, we reflect on the measurement of recall in rankings from a formal perspective.
• Pseudo-Labeling for Kernel Ridge Regression under Covariate Shift
  20 Feb 2023 1 repository listed Syntology ran 0 of 3 samples · 3 unverified
  We develop and analyze a principled approach to kernel ridge regression under covariate shift.
• Multi-label learning with missing labels using sparse global structure for label-specific features
  24 Jan 2023 1 repository listed
  Multi-label learning associates a given data instance with one or several class labels.
• Label Structure Preserving Contrastive Embedding for Multi-Label Learning with Missing Labels
  3 Sep 2022 1 repository listed
  However, these CL methods fail to be directly adapted to multi-label image classification due to the difficulty in defining the positive and negative instances to contrast a given anchor image in multi-label scenario,…
• Contrastive Learning for Online Semi-Supervised General Continual Learning
  12 Jul 2022 1 repository listed
  We study Online Continual Learning with missing labels and propose SemiCon, a new contrastive loss designed for partly labeled data.

Syntology lines on 8 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.