Short Text Clustering

Benchmarks archive 2025-07-28

8 leaderboard tables shown for this task, 8 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

2 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

18 shown of 18 papers with code (34 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.

• Short Text Clustering via Convolutional Neural Networks
  1 Jun 2015 3 repositories listed
• Twin Contrastive Learning for Online Clustering
  21 Oct 2022 2 repositories listed
  Specifically, we find that when the data is projected into a feature space with a dimensionality of the target cluster number, the rows and columns of its feature matrix correspond to the instance and cluster…
• Supporting Clustering with Contrastive Learning
  24 Mar 2021 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Unsupervised clustering aims at discovering the semantic categories of data according to some distance measured in the representation space.
• Discovering New Intents with Deep Aligned Clustering
  16 Dec 2020 2 repositories listed
  In this work, we propose an effective method, Deep Aligned Clustering, to discover new intents with the aid of the limited known intent data.
• Reliable Pseudo-labeling via Optimal Transport with Attention for Short Text Clustering
  25 Jan 2025 1 repository listed
  By solving this OT problem, we can yield reliable pseudo-labels that simultaneously account for sample-to-sample semantic consistency and sample-to-cluster global structure information.
• Discriminative Representation learning via Attention-Enhanced Contrastive Learning for Short Text Clustering
  7 Jan 2025 1 repository listed
  Then, the former module uses the more discriminative consistent representation to produce reliable supervision information for assist clustering, while the latter module explores similarity relationships and consistent…
• Guiding Sentiment Analysis with Hierarchical Text Clustering: Analyzing the German X/Twitter Discourse on Face Masks in the 2020 COVID-19 Pandemic
  1 Aug 2024 1 repository listed
  Social media are a critical component of the information ecosystem during public health crises.
• Human-interpretable clustering of short-text using large language models
  12 May 2024 1 repository listed
  The generative LLM shows good agreement with the human reviewers, and is suggested as a means to bridge the `validation gap' which often exists between cluster production and cluster interpretation.
• Robust Representation Learning with Reliable Pseudo-labels Generation via Self-Adaptive Optimal Transport for Short Text Clustering
  23 May 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  To tackle the above issues, we propose a Robust Short Text Clustering (RSTC) model to improve robustness against imbalanced and noisy data.
• EASE: Entity-Aware Contrastive Learning of Sentence Embedding
  9 May 2022 1 repository listed Syntology ran 1 of 5 samples · 4 unverified
  We present EASE, a novel method for learning sentence embeddings via contrastive learning between sentences and their related entities.
• DECAF: Deep Extreme Classification with Label Features
  1 Aug 2021 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  This paper develops the DECAF algorithm that addresses these challenges by learning models enriched by label metadata that jointly learn model parameters and feature representations using deep networks and offer…
• ECLARE: Extreme Classification with Label Graph Correlations
  31 Jul 2021 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  This paper presents ECLARE, a scalable deep learning architecture that incorporates not only label text, but also label correlations, to offer accurate real-time predictions within a few milliseconds.
• Efficient Sparse Spherical k-Means for Document Clustering
  30 Jul 2021 1 repository listed
  Spherical k-Means is frequently used to cluster document collections because it performs reasonably well in many settings and is computationally efficient.
• Intent Mining from past conversations for conversational agent
  22 May 2020 1 repository listed
  In this paper, we present an intent discovery framework that involves 4 primary steps: Extraction of textual utterances from a conversation using a pre-trained domain agnostic Dialog Act Classifier (Data Extraction),…
• Enhancement of Short Text Clustering by Iterative Classification
  31 Jan 2020 1 repository listed
  Short text clustering is a challenging task due to the lack of signal contained in such short texts.
• Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement
  20 Nov 2019 1 repository listed
  Identifying new user intents is an essential task in the dialogue system.
• A Self-Training Approach for Short Text Clustering
  1 Aug 2019 1 repository listed
  Short text clustering is a challenging problem when adopting traditional bag-of-words or TF-IDF representations, since these lead to sparse vector representations of the short texts.
• Self-Taught Convolutional Neural Networks for Short Text Clustering
  1 Jan 2017 1 repository listed
  Short text clustering is a challenging problem due to its sparseness of text representation.

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.