Browse State-of-the-Art › Semi-Supervised Text Classification
Semi-Supervised Text Classification
23 papers with code · 2 benchmarks · 2 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
2 leaderboard tables shown for this task, 2 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.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| AG News (200 Labels) (3 rows) | FlowGMM | Semi-Supervised Learning with Normalizing Flows | code | Syntology ran 1 of 1 samples · 0 unverified | Compare |
| Yahoo! Answers (800 Labels) (3 rows) | FlowGMM | Semi-Supervised Learning with Normalizing Flows | code | Syntology ran 1 of 1 samples · 0 unverified | Compare |
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
23 shown of 23 papers with code (41 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.
-
16 Aug 2017 4 repositories listedLearning latent representations from long text sequences is an important first step in many natural language processing applications.
-
25 May 2016 4 repositories listedWe extend adversarial and virtual adversarial training to the text domain by applying perturbations to the word embeddings in a recurrent neural network rather than to the original input itself.
-
22 May 2023 2 repositories listed Syntology ran 4 of 5 samples · 1 unverifiedSemi-supervised learning (SSL) is a popular setting aiming to effectively utilize unlabelled data to improve model performance in downstream natural language processing (NLP) tasks.
-
20 May 2023 2 repositories listed Syntology ran 5 of 17 samples · 12 unverified · 17 pointer-only (licence)Many text mining models are constructed by fine-tuning a large deep pre-trained language model (PLM) in downstream tasks.
-
25 Apr 2020 2 repositories listedThis paper presents MixText, a semi-supervised learning method for text classification, which uses our newly designed data augmentation method called TMix.
-
30 Dec 2019 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)Normalizing flows transform a latent distribution through an invertible neural network for a flexible and pleasingly simple approach to generative modelling, while preserving an exact likelihood.
-
22 Apr 2019 2 repositories listedSuccessful application processing sequential data, such as text and speech, requires an improved generalization performance of recurrent neural networks (RNNs).
-
26 Feb 2018 2 repositories listedThe first, critical, task for these applications is classifying whether a personal health event was mentioned, which we call the (PHM) problem.
-
25 Nov 2024 1 repository listedTo address these limitations, we propose a novel method of contrastive multi-graph learning with neighbor hierarchical sifting for semi-supervised text classification, namely ConNHS.
-
23 Oct 2023 1 repository listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)However, existing approaches based on pseudo-labeling suffer from the issues of pseudo-label bias and error accumulation.
-
23 Oct 2023 1 repository listed Syntology ran 2 of 5 samples · 3 unverified · 5 pointer-only (licence)During crisis events, people often use social media platforms such as Twitter to disseminate information about the situation, warnings, advice, and support.
-
4 Oct 2023 1 repository listed Syntology ran 4 of 5 samples · 1 unverified · 1 pointer-only (licence)The main challenge is how to distinguish high-quality pseudo labels against the confirmation bias.
-
13 Jun 2023 1 repository listedTo alleviate the noisy information, we adapt a reasoning with uncertainty-based approach to rank the unlabeled texts based on the evidential support received from the labeled texts.
-
23 Oct 2022 1 repository listedSelf-training methods have been explored in recent years and have exhibited great performance in improving semi-supervised learning.
-
20 May 2022 1 repository listedSemi-supervised learning is a promising way to reduce the annotation cost for text-classification.
-
10 Apr 2022 1 repository listedOur ME-GCN can integrate a rich source of graph edge information of the entire text corpus.
-
30 Sep 2021 1 repository listedThis set is used to initialize the second classifier, to be further trained by the set of labeled documents.
-
12 Sep 2021 1 repository listedIn natural language processing (NLP), state-of-the-art (SOTA) semi-supervised learning (SSL) frameworks have shown great performance on deep pre-trained language models such as BERT, and are expected to significantly…
-
15 Apr 2021 1 repository listedConsistency training regularizes a model by enforcing predictions of original and perturbed inputs to be similar.
-
8 Sep 2020 1 repository listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)In this paper, we study bidirectional LSTM network for the task of text classification using both supervised and semi-supervised approaches.
-
23 Apr 2020 1 repository listedWe present semi-supervised models with data augmentation (SMDA), a semi-supervised text classification system to classify interactive affective responses.
-
5 Jun 2019 1 repository listed Syntology ran 0 of 2 samples · 2 unverifiedWe accompany this paper with code to pretrain and use VAMPIRE embeddings in downstream tasks.
-
22 Jan 2019 1 repository listedWe propose a novel and simple method for semi-supervised text classification.
Syntology lines on 8 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.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections