Odd One Out

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 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

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

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

12 shown of 12 papers with code (21 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.

• Scaling Language Models: Methods, Analysis & Insights from Training Gopher
  8 Dec 2021 3 repositories listed
  Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
• VICE: Variational Interpretable Concept Embeddings
  2 May 2022 2 repositories listed Syntology ran 7 of 10 samples · 3 unverified · 10 pointer-only (licence)
  This paper introduces Variational Interpretable Concept Embeddings (VICE), an approximate Bayesian method for embedding object concepts in a vector space using data collected from humans in a triplet odd-one-out task.
• Training Compute-Optimal Large Language Models
  29 Mar 2022 2 repositories listed Syntology ran 8 of 11 samples · 3 unverified · 4 pointer-only (licence)
  We investigate the optimal model size and number of tokens for training a transformer language model under a given compute budget.
• Do Saliency Models Detect Odd-One-Out Targets? New Datasets and Evaluations
  13 May 2020 2 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Furthermore, we investigate the effect of training state-of-the-art CNN-based saliency models on these types of stimuli and conclude that the additional training data does not lead to a significant improvement of their…
• Odd-One-Out: Anomaly Detection by Comparing with Neighbors
  28 Jun 2024 1 repository listed
  This paper introduces a novel anomaly detection (AD) problem that focuses on identifying `odd-looking' objects relative to the other instances in a given scene.
• Towards Generative Abstract Reasoning: Completing Raven's Progressive Matrix via Rule Abstraction and Selection
  18 Jan 2024 1 repository listed Syntology ran 6 of 7 samples · 1 unverified · 7 pointer-only (licence)
  In the odd-one-out task and two held-out configurations, RAISE can leverage acquired latent concepts and atomic rules to find the rule-breaking image in a matrix and handle problems with unseen combinations of rules and…
• One Self-Configurable Model to Solve Many Abstract Visual Reasoning Problems
  15 Dec 2023 1 repository listed Syntology ran 7 of 9 samples · 2 unverified · 9 pointer-only (licence)
  With the aim of developing universal learning systems in the AVR domain, we propose the unified model for solving Single-Choice Abstract visual Reasoning tasks (SCAR), capable of solving various single-choice AVR tasks,…
• Spot The Odd One Out: Regularized Complete Cycle Consistent Anomaly Detector GAN
  16 Apr 2023 1 repository listed
  This study presents an adversarial method for anomaly detection in real-world applications, leveraging the power of generative adversarial neural networks (GANs) through cycle consistency in reconstruction error.
• Human alignment of neural network representations
  2 Nov 2022 1 repository listed Syntology ran 2 of 2 samples · 0 unverified
  Linear transformations of neural network representations learned from behavioral responses from one dataset substantially improve alignment with human similarity judgments on the other two datasets.
• Tell me why! Explanations support learning relational and causal structure
  7 Dec 2021 1 repository listed
  Inferring the abstract relational and causal structure of the world is a major challenge for reinforcement-learning (RL) agents.
• Odd-One-Out Representation Learning
  14 Dec 2020 1 repository listed
  The effective application of representation learning to real-world problems requires both techniques for learning useful representations, and also robust ways to evaluate properties of representations.
• We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos
  12 Aug 2020 1 repository listed
  This allows our model to perform cognitive tasks such as set abstraction (which general concept is in common among a set of videos?

Syntology lines on 6 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.