Sentence Classification
104 papers with code • 6 benchmarks • 14 datasets
Benchmarks
These leaderboards are used to track progress in Sentence Classification
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Libraries
Use these libraries to find Sentence Classification models and implementationsDatasets
Pubmed
SciCite
PubMed RCT
PcMSP
Cards Against Humanity
E2E Refined
Most implemented papers
CLUE: A Chinese Language Understanding Evaluation Benchmark
CLUEbenchmark/CLUE
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COLING 2020
The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks.
IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding
indobenchmark/indonlu
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Asian Chapter of the Association for Computational Linguistics 2020
Although Indonesian is known to be the fourth most frequently used language over the internet, the research progress on this language in the natural language processing (NLP) is slow-moving due to a lack of available resources.
QNLP in Practice: Running Compositional Models of Meaning on a Quantum Computer
CQCL/qnlp_lorenz_etal_2021_resources
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Our aim in doing this is to take the first small steps in this unexplored research territory and pave the way for practical Quantum Natural Language Processing.
Rediscovering Hashed Random Projections for Efficient Quantization of Contextualized Sentence Embeddings
Training and inference on edge devices often requires an efficient setup due to computational limitations.
Densely Connected Bidirectional LSTM with Applications to Sentence Classification
xuhaiming1996/Densely-Connected-Bidirectional-LSTM
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Deep neural networks have recently been shown to achieve highly competitive performance in many computer vision tasks due to their abilities of exploring in a much larger hypothesis space.
ListOps: A Diagnostic Dataset for Latent Tree Learning
yikangshen/Ordered-Memory
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NAACL 2018
In this paper we introduce ListOps, a toy dataset created to study the parsing ability of latent tree models.
An Attention-Gated Convolutional Neural Network for Sentence Classification
fabyangliu/AGCNN_sentence_classification
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The classification of sentences is very challenging, since sentences contain the limited contextual information.
Jointly Learning to Label Sentences and Tokens
Learning to construct text representations in end-to-end systems can be difficult, as natural languages are highly compositional and task-specific annotated datasets are often limited in size.
Glyce: Glyph-vectors for Chinese Character Representations
ShannonAI/glyce
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NeurIPS 2019
However, due to the lack of rich pictographic evidence in glyphs and the weak generalization ability of standard computer vision models on character data, an effective way to utilize the glyph information remains to be found.
Taming Pretrained Transformers for Extreme Multi-label Text Classification
OctoberChang/X-Transformer
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However, naively applying deep transformer models to the XMC problem leads to sub-optimal performance due to the large output space and the label sparsity issue.
