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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 68516900 of 17610 papers

TitleStatusHype
PoPreRo: A New Dataset for Popularity Prediction of Romanian Reddit PostsCode0
Learning to Describe for Predicting Zero-shot Drug-Drug InteractionsCode0
Putting words in context: LSTM language models and lexical ambiguityCode0
Neural Text Generation from Structured Data with Application to the Biography DomainCode0
Neural spell-checker: Beyond words with synthetic data generationCode0
Scalable Educational Question Generation with Pre-trained Language ModelsCode0
LayoutLMv2: Multi-modal Pre-training for Visually-Rich Document UnderstandingCode0
M^2ConceptBase: A Fine-Grained Aligned Concept-Centric Multimodal Knowledge BaseCode0
LLaVA-VSD: Large Language-and-Vision Assistant for Visual Spatial DescriptionCode0
Neural Academic Paper GenerationCode0
Targeted Syntactic Evaluation of Language ModelsCode0
Modeling Fine-grained Information via Knowledge-aware Hierarchical Graph for Zero-shot Entity RetrievalCode0
Language Model is a Branch Predictor for Simultaneous Machine TranslationCode0
LayoutLMv3: Pre-training for Document AI with Unified Text and Image MaskingCode0
Target-specified Sequence Labeling with Multi-head Self-attention for Target-oriented Opinion Words ExtractionCode0
SCA: Improve Semantic Consistent in Unrestricted Adversarial Attacks via DDPM InversionCode0
Scaffolded input promotes atomic organization in the recurrent neural network language modelCode0
MaskPure: Improving Defense Against Text Adversaries with Stochastic PurificationCode0
Multilingual unsupervised sequence segmentation transfers to extremely low-resource languagesCode0
LAMP: A Language Model on the MapCode0
SBI-RAG: Enhancing Math Word Problem Solving for Students through Schema-Based Instruction and Retrieval-Augmented GenerationCode0
Leveraging Domain Knowledge for Inclusive and Bias-aware Humanitarian Response Entry ClassificationCode0
LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classificationCode0
Reframing linguistic bootstrapping as joint inference using visually-grounded grammar induction modelsCode0
Say What You Mean! Large Language Models Speak Too Positively about Negative Commonsense KnowledgeCode0
Task-Informed Anti-Curriculum by Masking Improves Downstream Performance on TextCode0
Pyramidal Recurrent Unit for Language ModelingCode0
Task Loss Estimation for Sequence PredictionCode0
Task Refinement Learning for Improved Accuracy and Stability of Unsupervised Domain AdaptationCode0
TaskSet: A Dataset of Optimization TasksCode0
Dialogue-adaptive Language Model Pre-training From Quality EstimationCode0
Positive concave deep equilibrium modelsCode0
RCMHA: Relative Convolutional Multi-Head Attention for Natural Language ModellingCode0
Pythia: AI-assisted Code Completion SystemCode0
SaudiBERT: A Large Language Model Pretrained on Saudi Dialect CorporaCode0
Reshaping Free-Text Radiology Notes Into Structured Reports With Generative TransformersCode0
LyapLock: Bounded Knowledge Preservation in Sequential Large Language Model EditingCode0
SATURN: SAT-based Reinforcement Learning to Unleash Language Model ReasoningCode0
Tree Transformer: Integrating Tree Structures into Self-AttentionCode0
Recurrent Highway Networks with Grouped Auxiliary MemoryCode0
Satori: Towards Proactive AR Assistant with Belief-Desire-Intention User ModelingCode0
Post-Hoc Reversal: Are We Selecting Models Prematurely?Code0
Trellis Networks for Sequence ModelingCode0
Re-framing Incremental Deep Language Models for Dialogue Processing with Multi-task LearningCode0
QASiNa: Religious Domain Question Answering using Sirah NabawiyahCode0
SATA: A Paradigm for LLM Jailbreak via Simple Assistive Task LinkageCode0
SAS: Self-Augmentation Strategy for Language Model Pre-trainingCode0
Says Who? Effective Zero-Shot Annotation of Focalization0
SB@GU at the Complex Word Identification 2018 Shared Task0
Scaffold-BPE: Enhancing Byte Pair Encoding for Large Language Models with Simple and Effective Scaffold Token Removal0
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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