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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

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Showing 16751–16800 of 17610 papers

TitleStatusHype
Syntax-based Multi-system Machine Translation—0
LanguageCrawl: A Generic Tool for Building Language Models Upon Common-Crawl—0
The SI TEDx-UM speech database: a new Slovenian Spoken Language Resource—0
Linguistically Inspired Language Model Augmentation for MT—0
Transfer-Based Learning-to-Rank Assessment of Medical Term Technicality—0
MoBiL: A Hybrid Feature Set for Automatic Human Translation Quality Assessment—0
SCALE: A Scalable Language Engineering ToolkitCode0
Higher Order Recurrent Neural Networks—0
The Z-loss: a shift and scale invariant classification loss belonging to the Spherical FamilyCode0
Comparing Fifty Natural Languages and Twelve Genetic Languages Using Word Embedding Language Divergence (WELD) as a Quantitative Measure of Language Distance—0
Word Ordering Without SyntaxCode0
The IBM 2016 English Conversational Telephone Speech Recognition System—0
OCR Error Correction Using Character Correction and Feature-Based Word Classification—0
Chinese Song Iambics Generation with Neural Attention-based Model—0
Fully Convolutional Recurrent Network for Handwritten Chinese Text Recognition—0
Improving LSTM-based Video Description with Linguistic Knowledge Mined from TextCode0
A Compositional Approach to Language Modeling—0
LSTM based Conversation ModelsCode0
Recurrent Batch NormalizationCode0
Neural Text Generation from Structured Data with Application to the Biography DomainCode0
The Anatomy of a Search and Mining System for Digital Archives—0
Semi-supervised Word Sense Disambiguation with Neural Models—0
Personalized Speech recognition on mobile devices—0
Low-rank passthrough neural networksCode0
Recursive Recurrent Nets with Attention Modeling for OCR in the Wild—0
Unsupervised word segmentation and lexicon discovery using acoustic word embeddings—0
A Latent Variable Recurrent Neural Network for Discourse Relation Language ModelsCode0
Segmental Recurrent Neural Networks for End-to-end Speech Recognition—0
Representation of linguistic form and function in recurrent neural networksCode0
Architectural Complexity Measures of Recurrent Neural Networks—0
Automated Word Prediction in Bangla Language Using Stochastic Language Models—0
Recurrent Neural Network GrammarsCode0
Domain Specific Author Attribution Based on Feedforward Neural Network Language ModelsCode0
On Training Bi-directional Neural Network Language Model with Noise Contrastive EstimationCode0
Authorship Attribution Using a Neural Network Language ModelCode0
Knowledge Transfer with Medical Language Embeddings—0
A Factorized Recurrent Neural Network based architecture for medium to large vocabulary Language Modelling—0
Character-Level Incremental Speech Recognition with Recurrent Neural NetworksCode0
Long Short-Term Memory-Networks for Machine ReadingCode0
Smoothing parameter estimation framework for IBM word alignment models—0
Political Speech GenerationCode0
Recurrent Memory Networks for Language ModelingCode0
Contrastive Entropy: A new evaluation metric for unnormalized language models—0
A Contextual Language Model to Improve Machine Translation of Pronouns by Re-ranking Translation Hypotheses—0
Improving Phrase-Based SMT Using Cross-Granularity Embedding Similarity—0
Sparse Non-negative Matrix Language Modeling—0
Re-assessing the Impact of SMT Techniques with Human Evaluation: a Case Study on English---Croatian—0
Feedforward Sequential Memory Networks: A New Structure to Learn Long-term Dependency—0
Backward and Forward Language Modeling for Constrained Sentence Generation—0
The 2015 Sheffield System for Transcription of Multi-Genre Broadcast Media—0
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All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified