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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 49014950 of 17610 papers

TitleStatusHype
Automated Generation and Tagging of Knowledge Components from Multiple-Choice QuestionsCode0
Grounding of Textual Phrases in Images by ReconstructionCode0
Differentially Private Steering for Large Language Model AlignmentCode0
Character-based Neural Networks for Sentence Pair ModelingCode0
Group and Shuffle: Efficient Structured Orthogonal ParametrizationCode0
GrowOVER: How Can LLMs Adapt to Growing Real-World Knowledge?Code0
G-Safeguard: A Topology-Guided Security Lens and Treatment on LLM-based Multi-agent SystemsCode0
G-SciEdBERT: A Contextualized LLM for Science Assessment Tasks in GermanCode0
Automated Privacy Information Annotation in Large Language Model InteractionsCode0
GTA: Gated Toxicity Avoidance for LM Performance PreservationCode0
Characterizing and Understanding the Behavior of Quantized Models for Reliable DeploymentCode0
Characterizing Learning Curves During Language Model Pre-Training: Learning, Forgetting, and StabilityCode0
Guiding In-Context Learning of LLMs through Quality Estimation for Machine TranslationCode0
Guiding Vision-Language Model Selection for Visual Question-Answering Across Tasks, Domains, and Knowledge TypesCode0
GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trickCode0
A Latent Variable Recurrent Neural Network for Discourse Relation Language ModelsCode0
Contextualized Semantic Distance between Highly Overlapped TextsCode0
A Novel Metric for Evaluating Semantics PreservationCode0
Characterizing Verbatim Short-Term Memory in Neural Language ModelsCode0
Character-Level Incremental Speech Recognition with Recurrent Neural NetworksCode0
DigiCall: A Benchmark for Measuring the Maturity of Digital Strategy through Company Earning CallsCode0
HalluDial: A Large-Scale Benchmark for Automatic Dialogue-Level Hallucination EvaluationCode0
HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model TrainingCode0
A Conversation is Worth A Thousand Recommendations: A Survey of Holistic Conversational Recommender SystemsCode0
Handling Massive N-Gram Datasets EfficientlyCode0
Character-Level Language Modeling with Deeper Self-AttentionCode0
Handwritten Code Recognition for Pen-and-Paper CS EducationCode0
HanTrans: An Empirical Study on Cross-Era Transferability of Chinese Pre-trained Language ModelCode0
Pre-training of Graph Augmented Transformers for Medication RecommendationCode0
Modeling Disclosive Transparency in NLP Application DescriptionsCode0
Automated Source Code Generation and Auto-completion Using Deep Learning: Comparing and Discussing Current Language-Model-Related ApproachesCode0
Harnessing Dataset Cartography for Improved Compositional Generalization in TransformersCode0
Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model ApproachCode0
A Resilient and Accessible Distribution-Preserving Watermark for Large Language ModelsCode0
Directed Beam Search: Plug-and-Play Lexically Constrained Language GenerationCode0
Harnessing the Power of Large Language Model for Uncertainty Aware Graph ProcessingCode0
ChartFormer: A Large Vision Language Model for Converting Chart Images into Tactile Accessible SVGsCode0
Improving the Data-efficiency of Reinforcement Learning by Warm-starting with LLMCode0
Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt DistillationCode0
CHARTOM: A Visual Theory-of-Mind Benchmark for Multimodal Large Language ModelsCode0
Haste Makes Waste: Evaluating Planning Abilities of LLMs for Efficient and Feasible Multitasking with Time Constraints Between ActionsCode0
HateBERT: Retraining BERT for Abusive Language Detection in EnglishCode0
HATE-ITA: New Baselines for Hate Speech Detection in ItalianCode0
Direct Output Connection for a High-Rank Language ModelCode0
AlcLaM: Arabic Dialectal Language ModelCode0
Efficient Attention via Pre-Scoring: Prioritizing Informative Keys in TransformersCode0
Health Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement LearningCode0
Heaps' Law in GPT-Neo Large Language Model Emulated CorporaCode0
DIS-CO: Discovering Copyrighted Content in VLMs Training DataCode0
Discourse structure interacts with reference but not syntax in neural language modelsCode0
Show:102550
← PrevPage 99 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