Long-tail learning with class descriptors

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 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

4 datasets 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.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

6 shown of 6 papers with code (6 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.

• Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss
  18 Jun 2019 7 repositories listed Syntology ran 2 of 11 samples · 9 unverified · 3 pointer-only (licence)
  Deep learning algorithms can fare poorly when the training dataset suffers from heavy class-imbalance but the testing criterion requires good generalization on less frequent classes.
• Decoupling Representation and Classifier for Long-Tailed Recognition
  21 Oct 2019 4 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  The long-tail distribution of the visual world poses great challenges for deep learning based classification models on how to handle the class imbalance problem.
• Large-Scale Long-Tailed Recognition in an Open World
  10 Apr 2019 2 repositories listed
  We define Open Long-Tailed Recognition (OLTR) as learning from such naturally distributed data and optimizing the classification accuracy over a balanced test set which include head, tail, and open classes.
• Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
  18 Sep 2023 1 repository listed Syntology ran 5 of 8 samples · 3 unverified · 8 pointer-only (licence)
  The fine-tuning paradigm in addressing long-tail learning tasks has sparked significant interest since the emergence of foundation models.
• From Generalized zero-shot learning to long-tail with class descriptors
  5 Apr 2020 1 repository listed
  Real-world data is predominantly unbalanced and long-tailed, but deep models struggle to recognize rare classes in the presence of frequent classes.
• Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders
  1 Jun 2019 1 repository listed
  Many approaches in generalized zero-shot learning rely on cross-modal mapping between the image feature space and the class embedding space.

Syntology lines on 3 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.