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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1220112250 of 17610 papers

TitleStatusHype
What Does it Mean for a Language Model to Preserve Privacy?0
The Dual Form of Neural Networks Revisited: Connecting Test Time Predictions to Training Patterns via Spotlights of AttentionCode1
Online Decision TransformerCode2
ProteinBERT: a universal deep-learning model of protein sequence and functionCode2
Describing image focused in cognitive and visual details for visually impaired people: An approach to generating inclusive paragraphs0
Improving Automatic Speech Recognition for Non-Native English with Transfer Learning and Language Model DecodingCode0
AdaPrompt: Adaptive Model Training for Prompt-based NLP0
Topic Discovery via Latent Space Clustering of Pretrained Language Model RepresentationsCode1
The Volcspeech system for the ICASSP 2022 multi-channel multi-party meeting transcription challenge0
Using a Language Model in a Kiosk Recommender System at Fast-Food Restaurants0
ECRECer: Enzyme Commission Number Recommendation and Benchmarking based on Multiagent Dual-core LearningCode1
HistBERT: A Pre-trained Language Model for Diachronic Lexical Semantic AnalysisCode0
DALL-Eval: Probing the Reasoning Skills and Social Biases of Text-to-Image Generation ModelsCode3
Differentiable N-gram Objective on Abstractive SummarizationCode0
TimeLMs: Diachronic Language Models from TwitterCode2
Self-Supervised Representation Learning for Speech Using Visual Grounding and Masked Language ModelingCode1
OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning FrameworkCode0
Cedille: A large autoregressive French language modelCode2
Red Teaming Language Models with Language ModelsCode1
Prompt-Guided Injection of Conformation to Pre-trained Protein Model0
Ethics, Rules of Engagement, and AI: Neural Narrative Mapping Using Large Transformer Language Models0
From Discrimination to Generation: Knowledge Graph Completion with Generative TransformerCode0
Data Scaling Laws in NMT: The Effect of Noise and Architecture0
Polyphonic pitch detection with convolutional recurrent neural networks0
Pre-Trained Language Models for Interactive Decision-MakingCode2
mSLAM: Massively multilingual joint pre-training for speech and text0
Formal Mathematics Statement Curriculum LearningCode2
GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Records0
Pop Quiz! Can a Large Language Model Help With Reverse Engineering?0
RescoreBERT: Discriminative Speech Recognition Rescoring with BERT0
Unified Scaling Laws for Routed Language ModelsCode1
What Has Been Enhanced in my Knowledge-Enhanced Language Model?Code1
Regression Transformer: Concurrent sequence regression and generation for molecular language modelingCode1
BEA-Base: A Benchmark for ASR of Spontaneous Hungarian0
Examining Scaling and Transfer of Language Model Architectures for Machine Translation0
Disaster Tweets Classification using BERT-Based Language Model0
Does Transliteration Help Multilingual Language Modeling?Code0
MVPTR: Multi-Level Semantic Alignment for Vision-Language Pre-Training via Multi-Stage LearningCode1
Schema-Free Dependency Parsing via Sequence Generation0
Neuro-Symbolic Language Modeling with Automaton-augmented RetrievalCode2
Neural-FST Class Language Model for End-to-End Speech Recognition0
Multiple-Source Domain Adaptation via Coordinated Domain Encoders and Paired ClassifiersCode0
Protum: A New Method For Prompt Tuning Based on "[MASK]"0
Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsCode6
Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language ModelCode3
Impact of representation matching with neural machine translationCode0
An Assessment of the Impact of OCR Noise on Language Models0
FiNCAT: Financial Numeral Claim Analysis ToolCode0
Internal Language Model Estimation Through Explicit Context Vector Learning for Attention-based Encoder-decoder ASR0
A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language ModelCode0
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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