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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1480114850 of 17610 papers

TitleStatusHype
An Effective Contextual Language Modeling Framework for Speech Summarization with Augmented Features0
LRG at SemEval-2020 Task 7: Assessing the Ability of BERT and Derivative Models to Perform Short-Edits based Humor Grading0
Syntactic Structure Distillation Pretraining For Bidirectional Encoders0
TIME: Text and Image Mutual-Translation Adversarial Networks0
Self-Training for Unsupervised Parsing with PRPN0
Unsupervised Relation Extraction from Language Models using Constrained Cloze Completion0
qDKT: Question-centric Deep Knowledge Tracing0
When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications0
Improving Segmentation for Technical Support ProblemsCode0
Living Machines: A study of atypical animacyCode0
Leveraging Text Data Using Hybrid Transformer-LSTM Based End-to-End ASR in Transfer Learning0
ASAPP-ASR: Multistream CNN and Self-Attentive SRU for SOTA Speech Recognition0
Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems0
Early Stage LM Integration Using Local and Global Log-Linear Combination0
Investigation of Large-Margin Softmax in Neural Language Modeling0
SciSight: Combining faceted navigation and research group detection for COVID-19 exploratory scientific search0
Iterative Pseudo-Labeling for Speech RecognitionCode0
Improving Proper Noun Recognition in End-to-End ASR By Customization of the MWER Loss Criterion0
Human Instruction-Following with Deep Reinforcement Learning via Transfer-Learning from Text0
Approaches to Improving Recognition of Underrepresented Named Entities in Hybrid ASR Systems0
The NTNU System at the Interspeech 2020 Non-Native Children's Speech ASR Challenge0
Yseop at SemEval-2020 Task 5: Cascaded BERT Language Model for Counterfactual Statement Analysis0
How much complexity does an RNN architecture need to learn syntax-sensitive dependencies?Code0
Towards classification parity across cohorts0
Contextualizing ASR Lattice Rescoring with Hybrid Pointer Network Language Model0
Challenges in Emotion Style Transfer: An Exploration with a Lexical Substitution PipelineCode0
You Do Not Need More Data: Improving End-To-End Speech Recognition by Text-To-Speech Data Augmentation0
Multi-agent Communication meets Natural Language: Synergies between Functional and Structural Language Learning0
Parallel Corpus Filtering via Pre-trained Language Models0
Towards Hate Speech Detection at Large via Deep Generative ModelingCode0
Large Scale Multi-Actor Generative Dialog Modeling0
A Mixture of h-1 Heads is Better than h Heads0
DiscreTalk: Text-to-Speech as a Machine Translation Problem0
AttViz: Online exploration of self-attention for transparent neural language modelingCode0
Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance ApproachCode0
Commonsense Evidence Generation and Injection in Reading Comprehension0
Neural Polysynthetic Language Modelling0
Toward Better Storylines with Sentence-Level Language Models0
How Context Affects Language Models' Factual Predictions0
Distilling Knowledge from Pre-trained Language Models via Text Smoothing0
Quantum Natural Language Processing on Near-Term Quantum Computers0
Temporal Common Sense Acquisition with Minimal Supervision0
Learning Architectures from an Extended Search Space for Language Modeling0
Token Manipulation Generative Adversarial Network for Text GenerationCode0
Autoencoding Pixies: Amortised Variational Inference with Graph Convolutions for Functional Distributional SemanticsCode0
Russian Natural Language Generation: Creation of a Language Modelling Dataset and Evaluation with Modern Neural ArchitecturesCode0
Distributional Discrepancy: A Metric for Unconditional Text GenerationCode0
Fast and Robust Unsupervised Contextual Biasing for Speech Recognition0
Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models0
A Comprehensive Survey of Grammar Error Correction0
Show:102550
← PrevPage 297 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