Learning Semantic Representations

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

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

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

19 shown of 19 papers with code (38 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.

• Topology-Aware Modeling for Unsupervised Simulation-to-Reality Point Cloud Recognition
  26 Jun 2025 1 repository listed
  Learning semantic representations from point sets of 3D object shapes is often challenged by significant geometric variations, primarily due to differences in data acquisition methods.
• Boosting Vulnerability Detection of LLMs via Curriculum Preference Optimization with Synthetic Reasoning Data
  9 Jun 2025 1 repository listed
  Large language models (LLMs) demonstrate considerable proficiency in numerous coding-related tasks; however, their capabilities in detecting software vulnerabilities remain limited.
• Can We Get Rid of Handcrafted Feature Extractors? SparseViT: Nonsemantics-Centered, Parameter-Efficient Image Manipulation Localization through Spare-Coding Transformer
  19 Dec 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Non-semantic features are context-irrelevant and manipulation-sensitive.
• PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders
  16 Aug 2024 1 repository listed
  These methods typically include an encoder accepting visible patches (normalized) and corresponding patch centers (position) as input, with the decoder accepting the output of the encoder and the centers (position) of…
• ParamReL: Learning Parameter Space Representation via Progressively Encoding Bayesian Flow Networks
  24 May 2024 1 repository listed
  Specifically, ParamReL proposes a \emph{self-}encoder to learn latent semantics directly from parameters, rather than from observations.
• NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining
  11 Oct 2023 1 repository listed Syntology ran 5 of 7 samples · 2 unverified
  In this work, we make key technical contributions that are tailored to the numerical properties of time-series data and allow the model to scale to large datasets, e.
• Neural Feature Learning in Function Space
  18 Sep 2023 1 repository listed
  We present a novel framework for learning system design with neural feature extractors.
• Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE
  24 Oct 2022 1 repository listed Syntology ran 0 of 20 samples · 20 unverified
  Here, we consider the problem of learning semantic representations of objects that are invariant to pose and location in a fully unsupervised manner.
• Seeing the advantage: visually grounding word embeddings to better capture human semantic knowledge
  21 Feb 2022 1 repository listed
  In this paper we create visually grounded word embeddings by combining English text and images and compare them to popular text-based methods, to see if visual information allows our model to better capture cognitive…
• Modeling User Behavior with Graph Convolution for Personalized Product Search
  12 Feb 2022 1 repository listed
  Our approach can be seamlessly integrated with existing latent space based methods and be potentially applied in any product retrieval method that uses purchase history to model user preferences.
• VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
  5 Dec 2021 1 repository listed Syntology ran 0 of 2 samples · 2 unverified
  Machine learning-based program analysis methods use variable name representations for a wide range of tasks, such as suggesting new variable names and bug detection.
• Learning cortical representations through perturbed and adversarial dreaming
  9 Sep 2021 1 repository listed Syntology ran 0 of 4 samples · 4 unverified
  We support this hypothesis by implementing a cortical architecture inspired by generative adversarial networks (GANs).
• Semantic sentence similarity: size does not always matter
  16 Jun 2021 1 repository listed
  This study addresses the question whether visually grounded speech recognition (VGS) models learn to capture sentence semantics without access to any prior linguistic knowledge.
• On Learning Semantic Representations for Million-Scale Free-Hand Sketches
  7 Jul 2020 1 repository listed
  Specifically, we use our dual-branch architecture as a universal representation framework to design two sketch-specific deep models: (i) We propose a deep hashing model for sketch retrieval, where a novel hashing loss…
• Neural Collective Entity Linking Based on Recurrent Random Walk Network Learning
  20 Jun 2019 1 repository listed
  However, most neural collective EL methods depend entirely upon neural networks to automatically model the semantic dependencies between different EL decisions, which lack of the guidance from external knowledge.
• Learning semantic sentence representations from visually grounded language without lexical knowledge
  27 Mar 2019 1 repository listed
  The system achieves state-of-the-art results on several of these benchmarks, which shows that a system trained solely on multimodal data, without assuming any word representations, is able to capture sentence level…
• Learning Semantic Representations for Novel Words: Leveraging Both Form and Context
  9 Nov 2018 1 repository listed
  The general problem setting is that word embeddings are induced on an unlabeled training corpus and then a model is trained that embeds novel words into this induced embedding space.
• Learning Semantic Representations for Unsupervised Domain Adaptation
  1 Jul 2018 1 repository listed
  Prior domain adaptation methods address this problem through aligning the global distribution statistics between source domain and target domain, but a drawback of prior methods is that they ignore the semantic…
• Multilingual Models for Compositional Distributed Semantics
  17 Apr 2014 1 repository listed
  We present a novel technique for learning semantic representations, which extends the distributional hypothesis to multilingual data and joint-space embeddings.

Syntology lines on 5 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.