Sentiment Analysis

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

45 leaderboard tables shown for this task, 42 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. 10 shown of 45 until expanded.

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

104 datasets whose archive record lists this task, ordered by the archive's paper count. 30 shown of 104 until expanded.

Subtasks archive 2025-07-28

12 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 1,509 papers with code (5,630 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.

• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
  11 Oct 2018 534 repositories listed Syntology ran 204 of 659 samples · 455 unverified · 149 pointer-only (licence)
  We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers.
• Convolutional Neural Networks for Sentence Classification
  25 Aug 2014 118 repositories listed Syntology ran 19 of 77 samples · 58 unverified · 15 pointer-only (licence)
  We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for sentence-level classification tasks.
• RoBERTa: A Robustly Optimized BERT Pretraining Approach
  26 Jul 2019 67 repositories listed Syntology ran 22 of 48 samples · 26 unverified · 23 pointer-only (licence)
  Language model pretraining has led to significant performance gains but careful comparison between different approaches is challenging.
• Universal Language Model Fine-tuning for Text Classification
  18 Jan 2018 66 repositories listed Syntology ran 2 of 5 samples · 3 unverified · 3 pointer-only (licence)
  Inductive transfer learning has greatly impacted computer vision, but existing approaches in NLP still require task-specific modifications and training from scratch.
• Bag of Tricks for Efficient Text Classification
  6 Jul 2016 65 repositories listed Syntology ran 2 of 9 samples · 7 unverified · 2 pointer-only (licence)
  This paper explores a simple and efficient baseline for text classification.
• Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
  23 Oct 2019 57 repositories listed Syntology ran 2 of 31 samples · 29 unverified
  Transfer learning, where a model is first pre-trained on a data-rich task before being fine-tuned on a downstream task, has emerged as a powerful technique in natural language processing (NLP).
• A Structured Self-attentive Sentence Embedding
  9 Mar 2017 52 repositories listed Syntology ran 4 of 10 samples · 6 unverified · 2 pointer-only (licence)
  This paper proposes a new model for extracting an interpretable sentence embedding by introducing self-attention.
• Deep contextualized word representations
  15 Feb 2018 46 repositories listed Syntology ran 23 of 58 samples · 35 unverified · 25 pointer-only (licence)
  We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.
• Well-Read Students Learn Better: On the Importance of Pre-training Compact Models
  23 Aug 2019 40 repositories listed Syntology ran 6 of 32 samples · 26 unverified
  Recent developments in natural language representations have been accompanied by large and expensive models that leverage vast amounts of general-domain text through self-supervised pre-training.
• DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
  2 Oct 2019 37 repositories listed Syntology ran 19 of 27 samples · 8 unverified
  As Transfer Learning from large-scale pre-trained models becomes more prevalent in Natural Language Processing (NLP), operating these large models in on-the-edge and/or under constrained computational training or…
• Domain-Adversarial Training of Neural Networks
  28 May 2015 37 repositories listed Syntology ran 33 of 52 samples · 19 unverified · 22 pointer-only (licence)
  Our approach is directly inspired by the theory on domain adaptation suggesting that, for effective domain transfer to be achieved, predictions must be made based on features that cannot discriminate between the…
• Character-level Convolutional Networks for Text Classification
  4 Sep 2015 30 repositories listed Syntology ran 4 of 20 samples · 16 unverified · 5 pointer-only (licence)
  This article offers an empirical exploration on the use of character-level convolutional networks (ConvNets) for text classification.
• XLNet: Generalized Autoregressive Pretraining for Language Understanding
  19 Jun 2019 27 repositories listed Syntology ran 10 of 24 samples · 14 unverified · 3 pointer-only (licence)
  With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling.
• Distributed Representations of Sentences and Documents
  16 May 2014 27 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  Its construction gives our algorithm the potential to overcome the weaknesses of bag-of-words models.
• Universal Sentence Encoder
  29 Mar 2018 24 repositories listed Syntology ran 1 of 22 samples · 21 unverified · 1 pointer-only (licence)
  For both variants, we investigate and report the relationship between model complexity, resource consumption, the availability of transfer task training data, and task performance.
• Language Models are Unsupervised Multitask Learners
  14 Feb 2019 21 repositories listed
  Natural language processing tasks, such as question answering, machine translation, reading comprehension, and summarization, are typically approached with supervised learning on taskspecific datasets.
• Pay Attention to MLPs
  17 May 2021 20 repositories listed Syntology ran 34 of 44 samples · 10 unverified · 11 pointer-only (licence)
  Transformers have become one of the most important architectural innovations in deep learning and have enabled many breakthroughs over the past few years.
• Unsupervised Data Augmentation for Consistency Training
  29 Apr 2019 20 repositories listed Syntology ran 15 of 52 samples · 37 unverified · 9 pointer-only (licence)
  In this work, we present a new perspective on how to effectively noise unlabeled examples and argue that the quality of noising, specifically those produced by advanced data augmentation methods, plays a crucial role in…
• ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators
  23 Mar 2020 19 repositories listed Syntology ran 26 of 40 samples · 14 unverified · 10 pointer-only (licence)
  Then, instead of training a model that predicts the original identities of the corrupted tokens, we train a discriminative model that predicts whether each token in the corrupted input was replaced by a generator sample…
• ERNIE: Enhanced Representation through Knowledge Integration
  19 Apr 2019 19 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  We present a novel language representation model enhanced by knowledge called ERNIE (Enhanced Representation through kNowledge IntEgration).
• EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks
  31 Jan 2019 16 repositories listed Syntology ran 2 of 13 samples · 11 unverified · 1 pointer-only (licence)
  We present EDA: easy data augmentation techniques for boosting performance on text classification tasks.
• Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
  28 Feb 2015 16 repositories listed Syntology ran 6 of 15 samples · 9 unverified · 6 pointer-only (licence)
  Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have obtained strong…
• How to Fine-Tune BERT for Text Classification?
  14 May 2019 15 repositories listed Syntology ran 6 of 18 samples · 12 unverified · 5 pointer-only (licence)
  Language model pre-training has proven to be useful in learning universal language representations.
• DeBERTa: Decoding-enhanced BERT with Disentangled Attention
  5 Jun 2020 14 repositories listed Syntology ran 4 of 13 samples · 9 unverified · 3 pointer-only (licence)
  Recent progress in pre-trained neural language models has significantly improved the performance of many natural language processing (NLP) tasks.
• A Theoretically Grounded Application of Dropout in Recurrent Neural Networks
  16 Dec 2015 14 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  Recent results at the intersection of Bayesian modelling and deep learning offer a Bayesian interpretation of common deep learning techniques such as dropout.
• FNet: Mixing Tokens with Fourier Transforms
  9 May 2021 12 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 1 pointer-only (licence)
  At longer input lengths, our FNet model is significantly faster: when compared to the "efficient" Transformers on the Long Range Arena benchmark, FNet matches the accuracy of the most accurate models, while outpacing…
• Nyströmformer: A Nyström-Based Algorithm for Approximating Self-Attention
  7 Feb 2021 10 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 1 pointer-only (licence)
  The scalability of Nystr\"{o}mformer enables application to longer sequences with thousands of tokens.
• TinyBERT: Distilling BERT for Natural Language Understanding
  23 Sep 2019 10 repositories listed Syntology ran 0 of 4 samples · 4 unverified · 4 pointer-only (licence)
  To accelerate inference and reduce model size while maintaining accuracy, we first propose a novel Transformer distillation method that is specially designed for knowledge distillation (KD) of the Transformer-based…
• NEZHA: Neural Contextualized Representation for Chinese Language Understanding
  31 Aug 2019 10 repositories listed
  The pre-trained language models have achieved great successes in various natural language understanding (NLU) tasks due to its capacity to capture the deep contextualized information in text by pre-training on…
• A C-LSTM Neural Network for Text Classification
  27 Nov 2015 10 repositories listed
  In this work, we combine the strengths of both architectures and propose a novel and unified model called C-LSTM for sentence representation and text classification.

Syntology lines on 27 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.