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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 2951–3000 of 17610 papers

TitleStatusHype
Language Models Are Implicitly ContinuousCode1
fairseq: A Fast, Extensible Toolkit for Sequence ModelingCode1
Language Models are Universal EmbeddersCode1
Analysis and Evaluation of Language Models for Word Sense DisambiguationCode1
Aladdin: Zero-Shot Hallucination of Stylized 3D Assets from Abstract Scene DescriptionsCode1
Explaining Relationships Between Scientific DocumentsCode1
Citekit: A Modular Toolkit for Large Language Model Citation GenerationCode1
ASR2K: Speech Recognition for Around 2000 Languages without AudioCode1
CITER: Collaborative Inference for Efficient Large Language Model Decoding with Token-Level RoutingCode1
CiteWorth: Cite-Worthiness Detection for Improved Scientific Document UnderstandingCode1
CRE-LLM: A Domain-Specific Chinese Relation Extraction Framework with Fine-tuned Large Language ModelCode1
Language Models are Unsupervised Multitask LearnersCode1
CityBench: Evaluating the Capabilities of Large Language Models for Urban TasksCode1
CREAM: Consistency Regularized Self-Rewarding Language ModelsCode1
Fast and Accurate Deep Bidirectional Language Representations for Unsupervised LearningCode1
FastAdaSP: Multitask-Adapted Efficient Inference for Large Speech Language ModelCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
Language Model Pre-Training with Sparse Latent TypingCode1
CriticEval: Evaluating Large Language Model as CriticCode1
Language Model Prior for Low-Resource Neural Machine TranslationCode1
Fast-R2D2: A Pretrained Recursive Neural Network based on Pruned CKY for Grammar Induction and Text RepresentationCode1
FastRE: Towards Fast Relation Extraction with Convolutional Encoder and Improved Cascade Binary Tagging FrameworkCode1
A semantic embedding space based on large language models for modelling human beliefsCode1
Neural Grapheme-to-Phoneme Conversion with Pre-trained Grapheme ModelsCode1
A Language Model based Framework for New Concept Placement in OntologiesCode1
Fast Vocabulary Transfer for Language Model CompressionCode1
Few-Shot Learning for Opinion SummarizationCode1
Language Models as Causal Effect GeneratorsCode1
Language Models Implement Simple Word2Vec-style Vector ArithmeticCode1
Language Modeling with Gated Convolutional NetworksCode1
Feature Structure Distillation with Centered Kernel Alignment in BERT TransferringCode1
Federated Learning for ASR based on Wav2vec 2.0Code1
Crafting Large Language Models for Enhanced InterpretabilityCode1
FedScale: Benchmarking Model and System Performance of Federated Learning at ScaleCode1
newsSweeper at SemEval-2020 Task 11: Context-Aware Rich Feature Representations For Propaganda ClassificationCode1
Dual Modality Prompt Tuning for Vision-Language Pre-Trained ModelCode1
CPT: Efficient Deep Neural Network Training via Cyclic PrecisionCode1
Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense DisambiguationCode1
CPLLM: Clinical Prediction with Large Language ModelsCode1
An Interpretable Ensemble of Graph and Language Models for Improving Search Relevance in E-CommerceCode1
CPM: A Large-scale Generative Chinese Pre-trained Language ModelCode1
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and GenerationCode1
Language Modeling with Editable External KnowledgeCode1
Few-shot Multimodal Sentiment Analysis based on Multimodal Probabilistic Fusion PromptsCode1
A Better Way to Do Masked Language Model ScoringCode1
FFAA: Multimodal Large Language Model based Explainable Open-World Face Forgery Analysis AssistantCode1
Bioformer: an efficient transformer language model for biomedical text miningCode1
Language Modeling Is CompressionCode1
AdaCAD: Adaptively Decoding to Balance Conflicts between Contextual and Parametric KnowledgeCode1
BioELECTRA:Pretrained Biomedical text Encoder using DiscriminatorsCode1
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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