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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 9701–9750 of 17610 papers

TitleStatusHype
What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages—0
Unlocking the Secrets of Linear Complexity Sequence Model from A Unified Perspective—0
Zero-Shot Dense Video Captioning by Jointly Optimizing Text and Moment—0
Zero-shot Entity and Tweet Characterization with Designed Conditional Prompts and Contexts—0
Word-Level Representation From Bytes For Language Modeling—0
Zero-shot Generalization in Dialog State Tracking through Generative Question Answering—0
Zero-shot Generation of Coherent Storybook from Plain Text Story using Diffusion Models—0
Zero-shot Hazard Identification in Autonomous Driving: A Case Study on the COOOL Benchmark—0
Zero-Shot Hierarchical Classification on the Common Procurement Vocabulary Taxonomy—0
Unlocking Video-LLM via Agent-of-Thoughts Distillation—0
xGQA: Cross-Lingual Visual Question Answering—0
Knowledge Injection into Dialogue Generation via Language Models—0
What represents ``style'' in authorship attribution?—0
Zero-shot information extraction from radiological reports using ChatGPT—0
Zero-Shot Learning Based Approach For Medieval Word Recognition Using Deep-Learned Features—0
Zero-Shot Learning of Language Models for Describing Human Actions Based on Semantic Compositionality of Actions—0
Zero-Shot Learning Over Large Output Spaces : Utilizing Indirect Knowledge Extraction from Large Language Models—0
Zero-Shot Listwise Document Reranking with a Large Language Model—0
Zero-shot Load Forecasting for Integrated Energy Systems: A Large Language Model-based Framework with Multi-task Learning—0
Unsupervised Learning on an Approximate Corpus—0
Zero-shot Object Navigation with Vision-Language Models Reasoning—0
Training-Free Action Recognition and Goal Inference with Dynamic Frame Selection—0
What Should Baby Models Read? Exploring Sample-Efficient Data Composition on Model Performance—0
What's in a Measurement? Using GPT-3 on SemEval 2021 Task 8 -- MeasEval—0
Zero-Shot Question Answering over Financial Documents using Large Language Models—0
What's in a Name? Beyond Class Indices for Image Recognition—0
Zero-shot Safety Prediction for Autonomous Robots with Foundation World Models—0
Zero-Shot Semantic Segmentation via Spatial and Multi-Scale Aware Visual Class Embedding—0
Word Midas Powered by StringNet: Discovering Lexicogrammatical Constructions in Situ—0
Zero-Shot Sharpness-Aware Quantization for Pre-trained Language Models—0
Zero-shot Text Classification With Generative Language Models—0
Unsupervised Melody Segmentation Based on a Nested Pitman-Yor Language Model—0
What's in your Head? Emergent Behaviour in Multi-Task Transformer Models—0
What’s in Your Head? Emergent Behaviour in Multi-Task Transformer Models—0
Adapting Long Context NLM for ASR Rescoring in Conversational Agents—0
Zero-Shot Video Question Answering with Procedural Programs—0
Zero-Shot Dense Retrieval with Embeddings from Relevance Feedback—0
Unsupervised Method for Improving Arabic Speech Recognition Systems—0
Unsupervised Morphological Tree Tokenizer—0
Zeroth-Order Optimization Finds Flat Minima—0
ZEROTOP: Zero-Shot Task-Oriented Semantic Parsing using Large Language Models—0
ZETA: Leveraging Z-order Curves for Efficient Top-k Attention—0
Unsupervised Morphology-Based Vocabulary Expansion—0
Unsupervised morph segmentation and statistical language models for vocabulary expansion—0
ZeroShotDataAug: Generating and Augmenting Training Data with ChatGPT—0
ZiGong 1.0: A Large Language Model for Financial Credit—0
Zipporah: a Fast and Scalable Data Cleaning System for Noisy Web-Crawled Parallel Corpora—0
Ziya-Visual: Bilingual Large Vision-Language Model via Multi-Task Instruction Tuning—0
XGPT: Cross-modal Generative Pre-Training for Image Captioning—0
Unsupervised Multilingual Sentence Embeddings for Parallel Corpus Mining—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