SOTAVerified

Language Modelling

A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.

Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.

Source: Wikipedia

Papers

Showing 1525115300 of 17610 papers

TitleStatusHype
Phrase-Level Class based Language Model for Mandarin Smart Speaker Query Recognition0
Enriching Medcial Terminology Knowledge Bases via Pre-trained Language Model and Graph Convolutional Network0
Commonsense Knowledge Mining from Pretrained ModelsCode0
A Surprisingly Effective Fix for Deep Latent Variable Modeling of TextCode0
An Unsupervised Query Rewriting Approach Using N-gram Co-occurrence Statistics to Find Similar Phrases in Large Text Corpora0
Aspect-Based Sentiment Analysis using BERT0
Language Modeling with Syntactic and Semantic Representation for Sentence Acceptability PredictionsCode0
The Seemingly (Un)systematic Linking Element in Danish0
Persistence pays off: Paying Attention to What the LSTM Gating Mechanism Persists0
Jointly Learning Author and Annotated Character N-gram Embeddings: A Case Study in Literary Text0
Resolving Pronouns for a Resource-Poor Language, Malayalam Using Resource-Rich Language, Tamil.0
Towards Accurate Text Verbalization for ASR Based on Audio Alignment0
Multi-lingual Wikipedia Summarization and Title Generation On Low Resource Corpus0
Multilingual Language Models for Named Entity Recognition in German and English0
Semantic Language Model for Tunisian Dialect0
Comparing MT Approaches for Text Normalization0
Enhancing Phrase-Based Statistical Machine Translation by Learning Phrase Representations Using Long Short-Term Memory Network0
A Syntactically Expressive Morphological Analyzer for Turkish0
Real Life Application of a Question Answering System Using BERT Language Model0
Repurposing Decoder-Transformer Language Models for Abstractive Summarization0
Global Entity Disambiguation with BERTCode1
Behavior Gated Language Models0
Explicit Cross-lingual Pre-training for Unsupervised Machine Translation0
Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment ClassificationCode0
Implicit Deep Latent Variable Models for Text GenerationCode0
Detect Camouflaged Spam Content via StoneSkipping: Graph and Text Joint Embedding for Chinese Character Variation RepresentationCode0
Linguistic Versus Latent Relations for Modeling Coherent Flow in ParagraphsCode0
Pre-training A Neural Language Model Improves The Sample Efficiency of an Emergency Room Classification Model0
Multi-Task Learning with Language Modeling for Question Generation0
Probing Representations Learned by Multimodal Recurrent and Transformer Models0
Translating Math Formula Images to LaTeX Sequences Using Deep Neural Networks with Sequence-level TrainingCode0
Adversarial Representation Learning for Text-to-Image Matching0
Unsupervised Domain Adaptation for Neural Machine Translation with Domain-Aware Feature EmbeddingsCode0
Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks0
FinBERT: Financial Sentiment Analysis with Pre-trained Language ModelsCode0
The Limitations of Stylometry for Detecting Machine-Generated Fake News0
Connecting and Comparing Language Model Interpolation Techniques0
Measuring Patent Claim Generation by Span Relevancy0
uniblock: Scoring and Filtering Corpus with Unicode Block InformationCode0
Towards Unsupervised Image Captioning with Shared Multimodal Embeddings0
Release Strategies and the Social Impacts of Language Models0
A framework for anomaly detection using language modeling, and its applications to finance0
Well-Read Students Learn Better: On the Importance of Pre-training Compact ModelsCode2
Training Optimus Prime, M.D.: Generating Medical Certification Items by Fine-Tuning OpenAI's gpt2 Transformer Model0
Neural Poetry: Learning to Generate Poems using Syllables0
Deep Learning Based Chatbot ModelsCode0
When Low Resource NLP Meets Unsupervised Language Model: Meta-pretraining Then Meta-learning for Few-shot Text ClassificationCode0
VL-BERT: Pre-training of Generic Visual-Linguistic RepresentationsCode1
Sequential Latent Spaces for Modeling the Intention During Diverse Image Captioning0
"Mask and Infill" : Applying Masked Language Model to Sentiment Transfer0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67Unverified
2GRUValidation perplexity53.78Unverified
3LSTMValidation perplexity52.73Unverified
4LSTMTest perplexity48.7Unverified
5Temporal CNNTest perplexity45.2Unverified
6TCNTest perplexity45.19Unverified
7GCNN-8Test perplexity44.9Unverified
8Neural cache model (size = 100)Test perplexity44.8Unverified
9Neural cache model (size = 2,000)Test perplexity40.8Unverified
10GPT-2 SmallTest perplexity37.5Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47Unverified
2Seq-U-NetTest perplexity107.95Unverified
3GRU (Bai et al., 2018)Test perplexity92.48Unverified
4R-TransformerTest perplexity84.38Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67Unverified
2HypernetworksBit per Character (BPC)1.34Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33Unverified
4LN HM-LSTMBit per Character (BPC)1.32Unverified
5ByteNetBit per Character (BPC)1.31Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25Unverified
8Large mLSTMBit per Character (BPC)1.24Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33Unverified
2OPT 125MTest perplexity32.26Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1Unverified
4OPT 1.3BTest perplexity19.55Unverified
5GPT-Neo 125MTest perplexity17.83Unverified
6OPT 2.7BTest perplexity17.81Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12Unverified
8GPT-Neo 1.3BTest perplexity11.46Unverified
9Transformer 125MTest perplexity10.7Unverified
10GPT-Neo 2.7BTest perplexity10.44Unverified