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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1460114650 of 17610 papers

TitleStatusHype
AttViz: Online exploration of self-attention for transparent neural language modelingCode0
Enabling Language Models to Fill in the BlanksCode1
Neural Polysynthetic Language Modelling0
Toward Better Storylines with Sentence-Level Language Models0
SOLOIST: Building Task Bots at Scale with Transfer Learning and Machine TeachingCode1
Commonsense Evidence Generation and Injection in Reading Comprehension0
How Context Affects Language Models' Factual Predictions0
Finding Universal Grammatical Relations in Multilingual BERTCode1
Distilling Knowledge from Pre-trained Language Models via Text Smoothing0
Temporal Common Sense Acquisition with Minimal Supervision0
Quantum Natural Language Processing on Near-Term Quantum Computers0
ContextNet: Improving Convolutional Neural Networks for Automatic Speech Recognition with Global ContextCode1
A Systematic Assessment of Syntactic Generalization in Neural Language ModelsCode1
Autoencoding Pixies: Amortised Variational Inference with Graph Convolutions for Functional Distributional SemanticsCode0
Token Manipulation Generative Adversarial Network for Text GenerationCode0
Learning Architectures from an Extended Search Space for Language Modeling0
Russian Natural Language Generation: Creation of a Language Modelling Dataset and Evaluation with Modern Neural ArchitecturesCode0
Discrete Optimization for Unsupervised Sentence Summarization with Word-Level ExtractionCode1
Distributional Discrepancy: A Metric for Unconditional Text GenerationCode0
Fast and Robust Unsupervised Contextual Biasing for Speech Recognition0
Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error CorrectionCode1
Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models0
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation EvaluationCode1
Simplifying Paragraph-level Question Generation via Transformer Language ModelsCode2
A Comprehensive Survey of Grammar Error Correction0
DagoBERT: Generating Derivational Morphology with a Pretrained Language ModelCode0
BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QACode1
A Simple Language Model for Task-Oriented DialogueCode1
Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question AnsweringCode1
Exploring and Predicting Transferability across NLP TasksCode1
A language score based output selection method for multilingual speech recognition0
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data0
UnifiedQA: Crossing Format Boundaries With a Single QA SystemCode1
Visually Grounded Continual Learning of Compositional PhrasesCode1
Synthesizer: Rethinking Self-Attention in Transformer ModelsCode1
On Faithfulness and Factuality in Abstractive SummarizationCode1
Permutation Equivariant Models for Compositional Generalization in LanguageCode1
Improving Neural Language Generation with Spectrum Control0
Machine Translation from Spoken Language to Sign Language using Pre-trained Language Model as Encoder0
Recognizing Semantic Relations by Combining Transformers and Fully Connected Models0
On Construction of the ASR-oriented Indian English Pronunciation Dictionary0
ThaiLMCut: Unsupervised Pretraining for Thai Word SegmentationCode1
Language Modeling with a General Second-Order RNN0
Japanese Realistic Textual Entailment Corpus0
Minority Positive Sampling for Switching Points - an Anecdote for the Code-Mixing Language Modeling0
Cross-sentence Pre-trained Model for Interactive QA matching0
Adapting BERT to Implicit Discourse Relation Classification with a Focus on Discourse Connectives0
Evaluating the Impact of Sub-word Information and Cross-lingual Word Embeddings on Mi'kmaq Language Modelling0
Evaluating Approaches to Personalizing Language Models0
Class-based LSTM Russian Language Model with Linguistic Information0
Show:102550
← PrevPage 293 of 353Next →

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