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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1295113000 of 17610 papers

TitleStatusHype
Autoregressive Linguistic Steganography Based on BERT and Consistency Coding0
A Roadmap for Big Model0
Evaluating Distributional Distortion in Neural Language Modeling0
Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?Code0
Multi-armed bandits for resource efficient, online optimization of language model pre-training: the use case of dynamic maskingCode0
Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion0
Token Dropping for Efficient BERT Pretraining0
Prompt-based System for Personality and Interpersonal Reactivity Prediction0
Linearizing Transformer with Key-Value Memory0
Towards Textual Out-of-Domain Detection without In-Domain Labels0
VLSP 2021 - ViMRC Challenge: Vietnamese Machine Reading Comprehension0
Better Language Model with Hypernym Class PredictionCode0
Enhancing Speech Recognition Decoding via Layer Aggregation0
Immersive Text Game and Personality Classification0
Distinguishing Non-natural from Natural Adversarial Samples for More Robust Pre-trained Language ModelCode0
HiStruct+: Improving Extractive Text Summarization with Hierarchical Structure Information0
Universal Conditional Masked Language Pre-training for Neural Machine Translation0
Triangular Transfer: Freezing the Pivot for Triangular Machine Translation0
TA-SBERT: Token Attention Sentence-BERT for Improving Sentence Representation0
Linking Theories and Methods in Cognitive Sciences via Joint Embedding of the Scientific Literature: The Example of Cognitive ControlCode0
Multi-Stage Prompting for Knowledgeable Dialogue Generation0
Geographic Adaptation of Pretrained Language ModelsCode0
Cross-Lingual Ability of Multilingual Masked Language Models: A Study of Language Structure0
Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective DistillationCode0
Evaluating the Text-to-SQL Capabilities of Large Language Models0
Training a Tokenizer for Free with Private Federated Learning0
UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQL0
Efficient Language Modeling with Sparse all-MLP0
CoNTACT: A Dutch COVID-19 Adapted BERT for Vaccine Hesitancy and Argumentation Detection0
Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-modal Knowledge Transfer0
Towards Visual-Prompt Temporal Answering Grounding in Medical Instructional Video0
Enabling Multimodal Generation on CLIP via Vision-Language Knowledge Distillation0
Are discrete units necessary for Spoken Language Modeling?0
Connecting Neural Response measurements & Computational Models of language: a non-comprehensive guide0
Internet-augmented language models through few-shot prompting for open-domain question answering0
Compilable Neural Code Generation with Compiler Feedback0
MVP: Multimodality-guided Visual Pre-training0
LEMON: LanguagE ModeL for Negative Sampling of Knowledge Graph Embeddings0
Sentence-Select: Large-Scale Language Model Data Selection for Rare-Word Speech Recognition0
HealthPrompt: A Zero-shot Learning Paradigm for Clinical Natural Language Processing0
A practical framework for multi-domain speech recognition and an instance sampling method to neural language modeling0
Extraction of Sleep Information from Clinical Notes of Patients with Alzheimer's Disease Using Natural Language Processing0
HyperPELT: Unified Parameter-Efficient Language Model Tuning for Both Language and Vision-and-Language Tasks0
Which side are you on? Insider-Outsider classification in conspiracy-theoretic social media0
Semantic-Preserving Linguistic Steganography by Pivot Translation and Semantic-Aware Bins Coding0
SkillNet-NLU: A Sparsely Activated Model for General-Purpose Natural Language Understanding0
Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models0
Leveraging Pre-trained BERT for Audio Captioning0
Unfreeze with Care: Space-Efficient Fine-Tuning of Semantic Parsing Models0
Deep Lexical Hypothesis: Identifying personality structure in natural language0
Show:102550
← PrevPage 260 of 353Next →

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