Auxiliary Learning

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Most implemented papers archive 2025-07-28

30 shown of 30 papers with code (100 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.

• Self-Supervised Generalisation with Meta Auxiliary Learning
  25 Jan 2019 4 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  The loss for the label-generation network incorporates the loss of the multi-task network, and so this interaction between the two networks can be seen as a form of meta learning with a double gradient.
• RL-I2IT: Image-to-Image Translation with Deep Reinforcement Learning
  24 Sep 2023 2 repositories listed
  The key feature in the RL-I2IT framework is to decompose a monolithic learning process into small steps with a lightweight model to progressively transform a source image successively to a target image.
• Enhancing Deep Knowledge Tracing with Auxiliary Tasks
  14 Feb 2023 2 repositories listed
  In this paper, we proposed \emph{AT-DKT} to improve the prediction performance of the original deep knowledge tracing model with two auxiliary learning tasks, i.
• AANG: Automating Auxiliary Learning
  27 May 2022 2 repositories listed Syntology ran 3 of 5 samples · 2 unverified · 5 pointer-only (licence)
  Auxiliary objectives, supplementary learning signals that are introduced to help aid learning on data-starved or highly complex end-tasks, are commonplace in machine learning.
• Learning Object Placements For Relational Instructions by Hallucinating Scene Representations
  23 Jan 2020 2 repositories listed
  One particular requirement for such robots is that they are able to understand spatial relations and can place objects in accordance with the spatial relations expressed by their user.
• SDF-TopoNet: A Two-Stage Framework for Tubular Structure Segmentation via SDF Pre-training and Topology-Aware Fine-Tuning
  14 Mar 2025 1 repository listed
  In the fine-tuning phase, we incorporate a dynamic adapter alongside a refined topological loss to ensure topological correctness while mitigating overfitting and computational overhead.
• SGTC: Semantic-Guided Triplet Co-training for Sparsely Annotated Semi-Supervised Medical Image Segmentation
  20 Dec 2024 1 repository listed
  To address these issues, we propose a novel Semantic-Guided Triplet Co-training (SGTC) framework, which achieves high-end medical image segmentation by only annotating three orthogonal slices of a few volumetric…
• When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning
  25 Jun 2024 1 repository listed
  We provide a theoretical analysis of the learning dynamics of observation reconstruction, latent self-prediction, and TD learning in the presence of distractions and observation functions under linear model assumptions.
• Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost
  9 May 2024 1 repository listed Syntology ran 13 of 15 samples · 2 unverified · 15 pointer-only (licence)
  We aim at exploiting additional auxiliary labels from an independent (auxiliary) task to boost the primary task performance which we focus on, while preserving a single task inference cost of the primary task.
• GeoAuxNet: Towards Universal 3D Representation Learning for Multi-sensor Point Clouds
  28 Mar 2024 1 repository listed
  In this paper, we propose geometry-to-voxel auxiliary learning to enable voxel representations to access point-level geometric information, which supports better generalisation of the voxel-based backbone with…
• Enhancing Molecular Property Prediction with Auxiliary Learning and Task-Specific Adaptation
  29 Jan 2024 1 repository listed
  Pretrained Graph Neural Networks have been widely adopted for various molecular property prediction tasks.
• A Survey on Cross-Domain Sequential Recommendation
  10 Jan 2024 1 repository listed
  Cross-domain sequential recommendation (CDSR) shifts the modeling of user preferences from flat to stereoscopic by integrating and learning interaction information from multiple domains at different granularities…
• Learning to Recover Spectral Reflectance from RGB Images
  4 Apr 2023 1 repository listed
  Instead of relying on naive end-to-end training, we also propose a novel architecture that integrates the physical relationship between the spectral reflectance and the corresponding RGB images into the network based on…
• MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models
  23 Mar 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Therefore, we propose MEta Loss TRansformer (MELTR), a plug-in module that automatically and non-linearly combines various loss functions to aid learning the target task via auxiliary learning.
• Auxiliary Learning as an Asymmetric Bargaining Game
  31 Jan 2023 1 repository listed Syntology ran 0 of 3 samples · 3 unverified
  Auxiliary learning is an effective method for enhancing the generalization capabilities of trained models, particularly when dealing with small datasets.
• Benchmark for Uncertainty & Robustness in Self-Supervised Learning
  23 Dec 2022 1 repository listed
  Self-Supervised Learning (SSL) is crucial for real-world applications, especially in data-hungry domains such as healthcare and self-driving cars.
• Counting with Adaptive Auxiliary Learning
  8 Mar 2022 1 repository listed
  This paper proposes an adaptive auxiliary task learning based approach for object counting problems.
• Improving CTC-based speech recognition via knowledge transferring from pre-trained language models
  22 Feb 2022 1 repository listed
  Recently, end-to-end automatic speech recognition models based on connectionist temporal classification (CTC) have achieved impressive results, especially when fine-tuned from wav2vec2.
• Auto-Lambda: Disentangling Dynamic Task Relationships
  7 Feb 2022 1 repository listed
  Unlike previous methods where task relationships are assumed to be fixed, Auto-Lambda is a gradient-based meta learning framework which explores continuous, dynamic task relationships via task-specific weightings, and…
• On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-identification
  11 Jan 2022 1 repository listed
  Visible-infrared person re-identification (VI-ReID) has been challenging due to the existence of large discrepancies between visible and infrared modalities.
• Auxiliary Learning for Self-Supervised Video Representation via Similarity-based Knowledge Distillation
  7 Dec 2021 1 repository listed
  Our experimental results show superior results to the state of the art on both UCF101 and HMDB51 datasets when pretraining on K100 in apple-to-apple comparisons.
• Efficient Multi-Task Auxiliary Learning: Selecting Auxiliary Data by Feature Similarity
  1 Nov 2021 1 repository listed
  Multi-task auxiliary learning utilizes a set of relevant auxiliary tasks to improve the performance of a primary task.
• Boost-RS: Boosted Embeddings for Recommender Systems and its Application to Enzyme-Substrate Interaction Prediction
  28 Sep 2021 1 repository listed
  We show that each of our auxiliary tasks boosts learning of the embedding vectors, and that contrastive learning using Boost-RS outperforms attribute concatenation and multi-label learning.
• Leveraging Auxiliary Tasks with Affinity Learning for Weakly Supervised Semantic Segmentation
  25 Jul 2021 1 repository listed
  Motivated by the significant inter-task correlation, we propose a novel weakly supervised multi-task framework termed as AuxSegNet, to leverage saliency detection and multi-label image classification as auxiliary tasks…
• Auxiliary Tasks and Exploration Enable ObjectNav
  8 Apr 2021 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  We instead re-enable a generic learned agent by adding auxiliary learning tasks and an exploration reward.
• Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning
  1 Mar 2021 1 repository listed
  Our method is learning to learn a primary task with various auxiliary tasks to improve generalization performance.
• Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs
  16 Jul 2020 1 repository listed
  Our proposed method is learning to learn a primary task by predicting meta-paths as auxiliary tasks.
• Auxiliary Learning by Implicit Differentiation
  22 Jun 2020 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  Two main challenges arise in this multi-task learning setting: (i) designing useful auxiliary tasks; and (ii) combining auxiliary tasks into a single coherent loss.
• Dataset2Vec: Learning Dataset Meta-Features
  27 May 2019 1 repository listed
  As a data-driven approach, meta-learning requires meta-features that represent the primary learning tasks or datasets, and are estimated traditonally as engineered dataset statistics that require expert domain knowledge…
• Deep Auxiliary Learning for Visual Localization and Odometry
  9 Mar 2018 1 repository listed
  We evaluate our proposed VLocNet on indoor as well as outdoor datasets and show that even our single task model exceeds the performance of state-of-the-art deep architectures for global localization, while achieving…

Syntology lines on 7 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.