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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 32513300 of 17610 papers

TitleStatusHype
A Tensorized Transformer for Language ModelingCode1
EMO: Earth Mover Distance Optimization for Auto-Regressive Language ModelingCode1
Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge DistillationCode1
Emergence of Social Norms in Generative Agent Societies: Principles and ArchitectureCode1
ConfliBERT: A Language Model for Political ConflictCode1
OPI@LT-EDI-ACL2022: Detecting Signs of Depression from Social Media Text using RoBERTa Pre-trained Language ModelsCode1
AESOP: Paraphrase Generation with Adaptive Syntactic ControlCode1
Connecting Language and Vision for Natural Language-Based Vehicle RetrievalCode1
Emergent Analogical Reasoning in Large Language ModelsCode1
EmojiLM: Modeling the New Emoji LanguageCode1
Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product OperatorsCode1
Enhancing Reasoning to Adapt Large Language Models for Domain-Specific ApplicationsCode1
Evolving Deep Neural NetworksCode1
ELI5: Long Form Question AnsweringCode1
Elephants Never Forget: Testing Language Models for Memorization of Tabular DataCode1
Eliciting Knowledge from Pretrained Language Models for Prototypical Prompt VerbalizerCode1
OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video RecognitionCode1
Ouroboros: On Accelerating Training of Transformer-Based Language ModelsCode1
ELMER: A Non-Autoregressive Pre-trained Language Model for Efficient and Effective Text GenerationCode1
Outline to Story: Fine-grained Controllable Story Generation from Cascaded EventsCode1
ELECTRAMed: a new pre-trained language representation model for biomedical NLPCode1
Elastic Weight Removal for Faithful and Abstractive Dialogue GenerationCode1
ELECTRA: Pre-training Text Encoders as Discriminators Rather Than GeneratorsCode1
Efficient recurrent architectures through activity sparsity and sparse back-propagation through timeCode1
Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language ModelsCode1
Augmenting Interpretable Models with LLMs during TrainingCode1
PaLI-3 Vision Language Models: Smaller, Faster, StrongerCode1
EfficientVLM: Fast and Accurate Vision-Language Models via Knowledge Distillation and Modal-adaptive PruningCode1
Efficient Online Data Mixing For Language Model Pre-TrainingCode1
Efficient Pre-training of Masked Language Model via Concept-based Curriculum MaskingCode1
Atla Selene Mini: A General Purpose Evaluation ModelCode1
Efficient Nearest Neighbor Language ModelsCode1
Efficient Neural Architecture Search via Parameter SharingCode1
Human Sentence Processing: Recurrence or Attention?Code1
Confidence Estimation for Attention-based Sequence-to-sequence Models for Speech RecognitionCode1
SpeechPrompt: An Exploration of Prompt Tuning on Generative Spoken Language Model for Speech Processing TasksCode1
Efficiently Modeling Long Sequences with Structured State SpacesCode1
Efficient OCR for Building a Diverse Digital HistoryCode1
Parameter-Efficient Fine-Tuning of State Space ModelsCode1
Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language ModelsCode1
EGFI: Drug-Drug Interaction Extraction and Generation with Fusion of Enriched Entity and Sentence InformationCode1
BiasEdit: Debiasing Stereotyped Language Models via Model EditingCode1
Parsing as PretrainingCode1
ComPEFT: Compression for Communicating Parameter Efficient Updates via Sparsification and QuantizationCode1
Efficient Hierarchical Domain Adaptation for Pretrained Language ModelsCode1
Bias-Augmented Consistency Training Reduces Biased Reasoning in Chain-of-ThoughtCode1
Efficient Content-Based Sparse Attention with Routing TransformersCode1
Paying More Attention to Image: A Training-Free Method for Alleviating Hallucination in LVLMsCode1
Efficient Dynamic Clustering-Based Document Compression for Retrieval-Augmented-GenerationCode1
Effect of Pre-Training Scale on Intra- and Inter-Domain Full and Few-Shot Transfer Learning for Natural and Medical X-Ray Chest ImagesCode1
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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