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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 42014250 of 17610 papers

TitleStatusHype
Error Detection for Text-to-SQL Semantic ParsingCode0
Error-preserving Automatic Speech Recognition of Young English Learners' LanguageCode0
A Simple Way to Initialize Recurrent Networks of Rectified Linear UnitsCode0
Analysing Word Representation from the Input and Output Embeddings in Neural Network Language ModelsCode0
Agentic Reasoning: Reasoning LLMs with Tools for the Deep ResearchCode0
ESM-NBR: fast and accurate nucleic acid-binding residue prediction via protein language model feature representation and multi-task learningCode0
ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural NetworkCode0
Biased Importance Sampling for Deep Neural Network TrainingCode0
Estimating Large Language Model Capabilities without Labeled Test DataCode0
Context-Driven Interactive Query Simulations Based on Generative Large Language ModelsCode0
Context-Free Transductions with Neural StacksCode0
BiasKG: Adversarial Knowledge Graphs to Induce Bias in Large Language ModelsCode0
Why gradient clipping accelerates training: A theoretical justification for adaptivityCode0
Agentic Society: Merging skeleton from real world and texture from Large Language ModelCode0
A City of Millions: Mapping Literary Social Networks At ScaleCode0
Context Retrieval via Normalized Contextual Latent Interaction for Conversational AgentCode0
ETHAN at SemEval-2020 Task 5: Modelling Causal Reasoning inLanguage using neuro-symbolic cloud computingCode0
Bidirectional Attention as a Mixture of Continuous Word ExpertsCode0
Ask Question First for Enhancing Lifelong Language LearningCode0
Contextual Augmentation: Data Augmentation by Words with Paradigmatic RelationsCode0
Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm RepresentationCode0
Eureka-Moments in Transformers: Multi-Step Tasks Reveal Softmax Induced Optimization ProblemsCode0
ASMA-Tune: Unlocking LLMs' Assembly Code Comprehension via Structural-Semantic Instruction TuningCode0
Bidirectional Transformer Reranker for Grammatical Error CorrectionCode0
Contextual Emotion Recognition Using Transformer-Based ModelsCode0
Evaluating and Optimizing Educational Content with Large Language Model JudgmentsCode0
Contextual Grounding of Natural Language Entities in ImagesCode0
Evaluating Biases in Context-Dependent Health QuestionsCode0
Evaluating Class Membership Relations in Knowledge Graphs using Large Language ModelsCode0
Evaluating Commonsense in Pre-trained Language ModelsCode0
Evaluating context-invariance in unsupervised speech representationsCode0
Evaluating Cultural Adaptability of a Large Language Model via Simulation of Synthetic PersonasCode0
Evaluating Dependencies in Fact Editing for Language Models: Specificity and Implication AwarenessCode0
Evaluating Gender Bias in German Machine TranslationCode0
Analyzing constrained LLM through PDFA-learningCode0
Aspects of human memory and Large Language ModelsCode0
Contextualized Word Representations for Reading ComprehensionCode0
Evaluating Language Model Character TraitsCode0
Evaluating Large Language Model Biases in Persona-Steered GenerationCode0
Bilateral Personalized Dialogue Generation with Contrastive LearningCode0
Evaluating Large Language Models with Human Feedback: Establishing a Swedish BenchmarkCode0
Evaluating Large Language Model with Knowledge Oriented Language Specific Simple Question AnsweringCode0
Dial-MAE: ConTextual Masked Auto-Encoder for Retrieval-based Dialogue SystemsCode0
Evaluating Methods for Extraction of Aspect Terms in Opinion Texts in Portuguese - the Challenges of Implicit AspectsCode0
Bilingual Alignment Pre-Training for Zero-Shot Cross-Lingual TransferCode0
Evaluating Sequence-to-Sequence Models for Handwritten Text RecognitionCode0
Contextual String Embeddings for Sequence LabelingCode0
Bilingual alignment transfers to multilingual alignment for unsupervised parallel text miningCode0
Evaluating the Data Model Robustness of Text-to-SQL Systems Based on Real User QueriesCode0
"Bilingual Expert" Can Find Translation ErrorsCode0
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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