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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 54515500 of 17610 papers

TitleStatusHype
Unified Lexical Representation for Interpretable Visual-Language AlignmentCode0
Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse FinetuningCode0
Unified Modeling Language Code Generation from Diagram Images Using Multimodal Large Language ModelsCode0
Unified Representation for Non-compositional and Compositional ExpressionsCode0
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning FrameworkCode0
Unifying Global and Local Scene Entities Modelling for Precise Action SpottingCode0
Unifying Visual-Semantic Embeddings with Multimodal Neural Language ModelsCode0
UnihanLM: Coarse-to-Fine Chinese-Japanese Language Model Pretraining with the Unihan DatabaseCode0
UNIMELB at SemEval-2016 Tasks 4A and 4B: An Ensemble of Neural Networks and a Word2Vec Based Model for Sentiment ClassificationCode0
UniParma at SemEval-2021 Task 5: Toxic Spans Detection Using CharacterBERT and Bag-of-Words ModelCode0
Textless Speech-to-Speech Translation With Limited Parallel DataCode0
Universal Adversarial Triggers for Attacking and Analyzing NLPCode0
Universal Language Model Fine-Tuning with Subword Tokenization for PolishCode0
Universal TransformersCode0
Unknown Script: Impact of Script on Cross-Lingual TransferCode0
Unlearning Backdoor Attacks for LLMs with Weak-to-Strong Knowledge DistillationCode0
Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem SolvingCode0
Unlocking Efficiency: Adaptive Masking for Gene Transformer ModelsCode0
Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulator to Enhance Dialogue SystemCode0
Unraveling Feature Extraction Mechanisms in Neural NetworksCode0
Unsupervised Abstractive Summarization of Bengali Text DocumentsCode0
Unsupervised Boundary-Aware Language Model Pretraining for Chinese Sequence LabelingCode0
Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense RetrievalCode0
Unsupervised Contrast-Consistent Ranking with Language ModelsCode0
Unsupervised Document Expansion for Information Retrieval with Stochastic Text GenerationCode0
Unsupervised Domain Adaptation for Neural Machine Translation with Domain-Aware Feature EmbeddingsCode0
Unsupervised Domain Adaptation for Sparse Retrieval by Filling Vocabulary and Word Frequency GapsCode0
Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence LabelingCode0
Unsupervised Pretraining for Fact Verification by Language Model DistillationCode0
Unsupervised Improvement of Factual Knowledge in Language ModelsCode0
Where is the answer? Investigating Positional Bias in Language Model Knowledge ExtractionCode0
Unsupervised Neural Word Segmentation for Chinese via Segmental Language ModelingCode0
Unsupervised Recurrent Neural Network GrammarsCode0
Unsupervised Representation Learning of Player Behavioral Data with Confidence Guided MaskingCode0
Applying Unsupervised Semantic Segmentation to High-Resolution UAV Imagery for Enhanced Road Scene ParsingCode0
Unsupervised Sentence Representation Learning with Frequency-induced Adversarial Tuning and Incomplete Sentence FilteringCode0
Unsupervised Text Style Transfer using Language Models as DiscriminatorsCode0
Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent AgentsCode0
Unsupervised Word-level Quality Estimation for Machine Translation Through the Lens of Annotators (Dis)agreementCode0
Unsupervised Word Segmentation with Bi-directional Neural Language ModelCode0
Unveiling Environmental Impacts of Large Language Model Serving: A Functional Unit ViewCode0
Unveiling Gender Bias in Large Language Models: Using Teacher's Evaluation in Higher Education As an ExampleCode0
Unveiling Language Skills via Path-Level Circuit DiscoveryCode0
UPER: Boosting Multi-Document Summarization with an Unsupervised Prompt-based ExtractorCode0
Cross-Loss Influence Functions to Explain Deep Network RepresentationsCode0
Using Language Models to Improve Rule-based Linguistic Annotation of Modern Historical Japanese CorporaCode0
Using Language Model to Bootstrap Human Activity Recognition Ambient Sensors Based in Smart HomesCode0
Using Large Language Models for Student-Code Guided Test Case Generation in Computer Science EducationCode0
Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative StudyCode0
Utilizing Language Models to Expand Vision-Based Commonsense Knowledge GraphsCode0
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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