Multi-Label Classification

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

10 leaderboard tables shown for this task, 10 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

30 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

4 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 459 papers with code (1,198 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.

• Densely Connected Convolutional Networks
  25 Aug 2016 146 repositories listed Syntology ran 18 of 71 samples · 53 unverified · 7 pointer-only (licence)
  Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to the input and those close to the output.
• node2vec: Scalable Feature Learning for Networks
  3 Jul 2016 20 repositories listed Syntology ran 8 of 25 samples · 17 unverified · 3 pointer-only (licence)
  Taken together, our work represents a new way for efficiently learning state-of-the-art task-independent representations in complex networks.
• From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification
  5 Feb 2016 11 repositories listed Syntology ran 8 of 8 samples · 0 unverified · 2 pointer-only (licence)
  We propose sparsemax, a new activation function similar to the traditional softmax, but able to output sparse probabilities.
• Learning to diagnose from scratch by exploiting dependencies among labels
  28 Oct 2017 9 repositories listed
  The field of medical diagnostics contains a wealth of challenges which closely resemble classical machine learning problems; practical constraints, however, complicate the translation of these endpoints naively into…
• SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis
  12 May 2020 7 repositories listed
  In particular, the prediction of aspect-sentiment pairs is converted into multi-label classification, aiming to capture the dependency between words in a pair.
• Multi-Task Learning as Multi-Objective Optimization
  10 Oct 2018 7 repositories listed Syntology ran 2 of 19 samples · 17 unverified
  These algorithms are not directly applicable to large-scale learning problems since they scale poorly with the dimensionality of the gradients and the number of tasks.
• ImageNet-21K Pretraining for the Masses
  22 Apr 2021 5 repositories listed Syntology ran 1 of 2 samples · 1 unverified
  ImageNet-1K serves as the primary dataset for pretraining deep learning models for computer vision tasks.
• Asymmetric Loss For Multi-Label Classification
  29 Sep 2020 5 repositories listed Syntology ran 4 of 12 samples · 8 unverified · 7 pointer-only (licence)
  In this paper, we introduce a novel asymmetric loss ("ASL"), which operates differently on positive and negative samples.
• Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction
  29 Oct 2021 4 repositories listed Syntology ran 6 of 20 samples · 14 unverified
  We also provide a theoretical analysis that justifies the use of XMC over link prediction and motivates integrating XR-Transformers, a powerful method for solving XMC problems, into the GIANT framework.
• ML-Net: multi-label classification of biomedical texts with deep neural networks
  13 Nov 2018 4 repositories listed
  Due to this nature, the multi-label text classification task is often considered to be more challenging compared to the binary or multi-class text classification problems.
• Extremely Randomized CNets for Multi-label Classification
  1 Oct 2018 4 repositories listed
  Promising approaches for MLC are those able to capture label dependencies by learning a single probabilistic model—differently from other competitive approaches requiring to learn many models.
• SCDV : Sparse Composite Document Vectors using soft clustering over distributional representations
  20 Dec 2016 4 repositories listed
  We present a feature vector formation technique for documents - Sparse Composite Document Vector (SCDV) - which overcomes several shortcomings of the current distributional paragraph vector representations that are…
• PIDray: A Large-scale X-ray Benchmark for Real-World Prohibited Item Detection
  19 Nov 2022 3 repositories listed
  Automatic security inspection relying on computer vision technology is a challenging task in real-world scenarios due to many factors, such as intra-class variance, class imbalance, and occlusion.
• Deep Hierarchical Semantic Segmentation
  27 Mar 2022 3 repositories listed Syntology ran 1 of 5 samples · 4 unverified
  In this paper, we instead address hierarchical semantic segmentation (HSS), which aims at structured, pixel-wise description of visual observation in terms of a class hierarchy.
• Query2Label: A Simple Transformer Way to Multi-Label Classification
  22 Jul 2021 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  The use of Transformer is rooted in the need of extracting local discriminative features adaptively for different labels, which is a strongly desired property due to the existence of multiple objects in one image.
• Distribution-Free, Risk-Controlling Prediction Sets
  7 Jan 2021 3 repositories listed Syntology ran 3 of 3 samples · 0 unverified
  While improving prediction accuracy has been the focus of machine learning in recent years, this alone does not suffice for reliable decision-making.
• TResNet: High Performance GPU-Dedicated Architecture
  30 Mar 2020 3 repositories listed
  In this work, we introduce a series of architecture modifications that aim to boost neural networks' accuracy, while retaining their GPU training and inference efficiency.
• Multi-Label Classification with Label Graph Superimposing
  21 Nov 2019 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  In this paper, we propose a label graph superimposing framework to improve the conventional GCN+CNN framework developed for multi-label recognition in the following two aspects.
• Ludwig: a type-based declarative deep learning toolbox
  17 Sep 2019 3 repositories listed
  In this work we present Ludwig, a flexible, extensible and easy to use toolbox which allows users to train deep learning models and use them for obtaining predictions without writing code.
• Bonsai -- Diverse and Shallow Trees for Extreme Multi-label Classification
  17 Apr 2019 3 repositories listed
  In this paper, we develop a suite of algorithms, called Bonsai, which generalizes the notion of label representation in XMC, and partitions the labels in the representation space to learn shallow trees.
• Neural Fine-Grained Entity Type Classification with Hierarchy-Aware Loss
  9 Mar 2018 3 repositories listed
  The task of Fine-grained Entity Type Classification (FETC) consists of assigning types from a hierarchy to entity mentions in text.
• Learning Approximate Inference Networks for Structured Prediction
  9 Mar 2018 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)
  Prior work used gradient descent for inference, relaxing the structured output to a set of continuous variables and then optimizing the energy with respect to them.
• Semantic Operators: A Declarative Model for Rich, AI-based Data Processing
  16 Jul 2024 2 repositories listed
  Our model specifies the expected behavior of each operator with a high-quality gold algorithm, and we develop an optimization framework that reduces cost, while providing accuracy guarantees with respect to a gold…
• XTrack: Multimodal Training Boosts RGB-X Video Object Trackers
  28 May 2024 2 repositories listed
  Technically, we achieve this by routing samples from one modality to the expert of the others, within a mixture-of-experts framework designed for multimodal video object tracking.
• Expanding the Horizon: Enabling Hybrid Quantum Transfer Learning for Long-Tailed Chest X-Ray Classification
  30 Apr 2024 2 repositories listed
  We evaluated the performance of our Jax-based framework in terms of efficiency and performance for hybrid quantum transfer learning for long-tailed classification across 8, 14, and 19 disease labels using large-scale…
• VHM: Versatile and Honest Vision Language Model for Remote Sensing Image Analysis
  29 Mar 2024 2 repositories listed Syntology ran 2 of 4 samples · 2 unverified
  VHM is built on a large-scale remote sensing image-text dataset with rich-content captions (VersaD), and an honest instruction dataset comprising both factual and deceptive questions (HnstD).
• Consistent algorithms for multi-label classification with macro-at-k metrics
  29 Jan 2024 2 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  We consider the optimization of complex performance metrics in multi-label classification under the population utility framework.
• A Comparative Analysis of Noise Reduction Methods in Sentiment Analysis on Noisy Bangla Texts
  25 Jan 2024 2 repositories listed
  In this paper, we introduce a dataset (NC-SentNoB) that we annotated manually to identify ten different types of noise found in a pre-existing sentiment analysis dataset comprising of around 15K noisy Bangla texts.
• In-Context Learning for Extreme Multi-Label Classification
  22 Jan 2024 2 repositories listed
  Multi-label classification problems with thousands of classes are hard to solve with in-context learning alone, as language models (LMs) might lack prior knowledge about the precise classes or how to assign them, and it…
• Category-Wise Fine-Tuning for Image Multi-label Classification with Partial Labels
  27 Nov 2023 2 repositories listed
  A single model submitted to the competition server for the official evaluation achieves mAUC 91.

Syntology lines on 14 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.