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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 9051–9100 of 17610 papers

TitleStatusHype
Large Language Models for Dysfluency Detection in Stuttered Speech—0
Large Language Models for Judicial Entity Extraction: A Comparative Study—0
Large Language Models for Medical Forecasting -- Foresight 2—0
Large Language Models for Single-Step and Multi-Step Flight Trajectory Prediction—0
Large Language Models For Text Classification: Case Study And Comprehensive Review—0
Large Language Model Should Understand Pinyin for Chinese ASR Error Correction—0
Large language models implicitly learn to straighten neural sentence trajectories to construct a predictive representation of natural language—0
Large language models improve Alzheimer's disease diagnosis using multi-modality data—0
Large Language Model Soft Ideologization via AI-Self-Consciousness—0
Large Language Models on the Chessboard: A Study on ChatGPT's Formal Language Comprehension and Complex Reasoning Skills—0
Large Language Model Strategic Reasoning Evaluation through Behavioral Game Theory—0
Large Language Model Supply Chain: Open Problems From the Security Perspective—0
Large Language Model Watermark Stealing With Mixed Integer Programming—0
Large Language Model with Graph Convolution for Recommendation—0
Large Malaysian Language Model Based on Mistral for Enhanced Local Language Understanding—0
Large Margin Neural Language Model—0
Large Model driven Radiology Report Generation with Clinical Quality Reinforcement Learning—0
Large Multimodal Models: Notes on CVPR 2023 Tutorial—0
LargePiG: Your Large Language Model is Secretly a Pointer Generator—0
Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All—0
Large, Pruned or Continuous Space Language Models on a GPU for Statistical Machine Translation—0
Larger-Context Language Modelling—0
Larger-Context Language Modelling with Recurrent Neural Network—0
Larger-Scale Transformers for Multilingual Masked Language Modeling—0
Large-scale Analysis of Counseling Conversations: An Application of Natural Language Processing to Mental Health—0
Large-scale Cloze Test Dataset Created by Teachers—0
Large-scale Dictionary Construction via Pivot-based Statistical Machine Translation with Significance Pruning and Neural Network Features—0
Large-Scale Differentially Private BERT—0
Large-scale discriminative language model reranking for voice-search—0
Large-Scale Discriminative Training for Statistical Machine Translation Using Held-Out Line Search—0
Large scale distributed neural network training through online distillation—0
Large-scale Exact Decoding: The IMS-TTT submission to WMT14—0
Large-scale Language Model Rescoring on Long-form Data—0
Large Scale Legal Text Classification Using Transformer Models—0
Large Scale Multi-Actor Generative Dialog Modeling—0
Large-Scale Multi-Document Summarization with Information Extraction and Compression—0
Large-Scale News Classification using BERT Language Model: Spark NLP Approach—0
Large-scale Pretraining Improves Sample Efficiency of Active Learning based Molecule Virtual Screening—0
Large-Scale Self- and Semi-Supervised Learning for Speech Translation—0
Large-Scale Syntactic Language Modeling with Treelets—0
Large-Scale Text Analysis Using Generative Language Models: A Case Study in Discovering Public Value Expressions in AI Patents—0
Large Search Model: Redefining Search Stack in the Era of LLMs—0
Large, Small or Both: A Novel Data Augmentation Framework Based on Language Models for Debiasing Opinion Summarization—0
Large Vision-Language Model Alignment and Misalignment: A Survey Through the Lens of Explainability—0
Large Vision-Language Models for Remote Sensing Visual Question Answering—0
Large Vocabulary Arabic Online Handwriting Recognition System—0
Large Vocabulary Size Improves Large Language Models—0
Large Vocabulary Spontaneous Speech Recognition for Tigrigna—0
LARM: Large Auto-Regressive Model for Long-Horizon Embodied Intelligence—0
LARR: Large Language Model Aided Real-time Scene Recommendation with Semantic Understanding—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