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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 36513700 of 17610 papers

TitleStatusHype
Outline to Story: Fine-grained Controllable Story Generation from Cascaded EventsCode1
CDLM: Cross-Document Language ModelingCode1
KM-BART: Knowledge Enhanced Multimodal BART for Visual Commonsense GenerationCode1
BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in BanglaCode1
Discovering Autoregressive Orderings with Variational InferenceCode1
Not All Memories are Created Equal: Learning to ExpireCode1
K-PLUG: KNOWLEDGE-INJECTED PRE-TRAINED LANGUAGE MODEL FOR NATURAL LANGUAGE UNDERSTANDING AND GENERATIONCode1
Subformer: Exploring Weight Sharing for Parameter Efficiency in Generative TransformersCode1
WARP: Word-level Adversarial ReProgrammingCode1
AraGPT2: Pre-Trained Transformer for Arabic Language GenerationCode1
AraELECTRA: Pre-Training Text Discriminators for Arabic Language UnderstandingCode1
Shortformer: Better Language Modeling using Shorter InputsCode1
Unified Mandarin TTS Front-end Based on Distilled BERT ModelCode1
ECONET: Effective Continual Pretraining of Language Models for Event Temporal ReasoningCode1
Generating Query Focused Summaries from Query-Free ResourcesCode1
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-TuningCode1
Cross-domain Retrieval in the Legal and Patent Domains: a Reproducibility StudyCode1
RealFormer: Transformer Likes Residual AttentionCode1
Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-TrainingCode1
BERT Goes Shopping: Comparing Distributional Models for Product RepresentationsCode1
Extracting Training Data from Large Language ModelsCode1
Binary Black-box Evasion Attacks Against Deep Learning-based Static Malware Detectors with Adversarial Byte-Level Language ModelCode1
Towards Neural Programming InterfacesCode1
Fusing Context Into Knowledge Graph for Commonsense Question AnsweringCode1
TAP: Text-Aware Pre-training for Text-VQA and Text-CaptionCode1
UBAR: Towards Fully End-to-End Task-Oriented Dialog Systems with GPT-2Code1
Pre-training Protein Language Models with Label-Agnostic Binding Pairs Enhances Performance in Downstream TasksCode1
CPM: A Large-scale Generative Chinese Pre-trained Language ModelCode1
End-to-End Automatic Speech Recognition for GujaratiCode1
Multi-Task Learning for Knowledge Graph Completion with Pre-trained Language ModelsCode1
Scale down Transformer by Grouping Features for a Lightweight Character-level Language ModelCode1
Arabisc: Context-Sensitive Neural Spelling CheckerCode1
Try to Substitute: An Unsupervised Chinese Word Sense Disambiguation Method Based on HowNetCode1
Retrieving Skills from Job Descriptions: A Language Model Based Extreme Multi-label Classification FrameworkCode1
SentiX: A Sentiment-Aware Pre-Trained Model for Cross-Domain Sentiment AnalysisCode1
Enhancing Clinical BERT Embedding using a Biomedical Knowledge BaseCode1
StructFormer: Joint Unsupervised Induction of Dependency and Constituency Structure from Masked Language ModelingCode1
TableGPT: Few-shot Table-to-Text Generation with Table Structure Reconstruction and Content MatchingCode1
Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-TaskLearning for Offensive Language DetectionCode1
The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modelingCode1
Unsupervised Domain Adaptation of a Pretrained Cross-Lingual Language ModelCode1
Neural Semi-supervised Learning for Text Classification Under Large-Scale PretrainingCode1
Learning Associative Inference Using Fast Weight MemoryCode1
Utilizing Bidirectional Encoder Representations from Transformers for Answer SelectionCode1
Context-aware Stand-alone Neural Spelling CorrectionCode1
Scaling Hidden Markov Language ModelsCode1
Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERTCode1
Adapting a Language Model for Controlled Affective Text GenerationCode1
Knowledge-driven Data Construction for Zero-shot Evaluation in Commonsense Question AnsweringCode1
Conditioned Text Generation with Transfer for Closed-Domain Dialogue SystemsCode1
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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