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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 1695117000 of 17610 papers

TitleStatusHype
Entity or Relation Embeddings? An Analysis of Encoding Strategies for Relation ExtractionCode0
HLM-Cite: Hybrid Language Model Workflow for Text-based Scientific Citation PredictionCode0
Breaking the Softmax Bottleneck: A High-Rank RNN Language ModelCode0
Cross-lingual Contextualized Phrase RetrievalCode0
Breaking the Silence: the Threats of Using LLMs in Software EngineeringCode0
Brain-Like Language Processing via a Shallow Untrained Multihead Attention NetworkCode0
Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical DataCode0
Entropy- and Distance-Based Predictors From GPT-2 Attention Patterns Predict Reading Times Over and Above GPT-2 SurprisalCode0
Improving Code Example Recommendations on Informal Documentation Using BERT and Query-Aware LSH: A Comparative StudyCode0
Independently Recurrent Neural Network (IndRNN): Building A Longer and Deeper RNNCode0
Applying a Pre-trained Language Model to Spanish Twitter Humor PredictionCode0
Into the crossfire: evaluating the use of a language model to crowdsource gun violence reportsCode0
A Dual Encoder Sequence to Sequence Model for Open-Domain Dialogue ModelingCode0
Into the Unknown: Generating Geospatial Descriptions for New EnvironmentsCode0
Cross-Lingual BERT Transformation for Zero-Shot Dependency ParsingCode0
Entry Separation using a Mixed Visual and Textual Language Model: Application to 19th century French Trade DirectoriesCode0
Environmental large language model Evaluation (ELLE) dataset: A Benchmark for Evaluating Generative AI applications in Eco-environment DomainCode0
BP-Transformer: Modelling Long-Range Context via Binary PartitioningCode0
APPLS: Evaluating Evaluation Metrics for Plain Language SummarizationCode0
Is a Single Vector Enough? Exploring Node Polysemy for Network EmbeddingCode0
Cross-lingual Argument Mining in the Medical DomainCode0
B-PROP: Bootstrapped Pre-training with Representative Words Prediction for Ad-hoc RetrievalCode0
Improving Complex Knowledge Base Question Answering via Question-to-Action and Question-to-Question AlignmentCode0
Aligning Language Models Using Follow-up Likelihood as Reward SignalCode0
Anti-LM Decoding for Zero-shot In-context Machine TranslationCode0
Gender Biases and Where to Find Them: Exploring Gender Bias in Pre-Trained Transformer-based Language Models Using Movement PruningCode0
Answer-level Calibration for Free-form Multiple Choice Question AnsweringCode0
Gender Encoding Patterns in Pretrained Language Model RepresentationsCode0
ERASMO: Leveraging Large Language Models for Enhanced Clustering SegmentationCode0
A Novel Metric for Evaluating Semantics PreservationCode0
ERNIE 3.0 Tiny: Frustratingly Simple Method to Improve Task-Agnostic Distillation GeneralizationCode0
Development and Validation of a Dynamic-Template-Constrained Large Language Model for Generating Fully-Structured Radiology ReportsCode0
Contextualized Semantic Distance between Highly Overlapped TextsCode0
Cross-Domain NER using Cross-Domain Language ModelingCode0
ERNIE-Doc: A Retrospective Long-Document Modeling TransformerCode0
CrossBind: Collaborative Cross-Modal Identification of Protein Nucleic-Acid-Binding ResiduesCode0
Is Attention All What You Need? -- An Empirical Investigation on Convolution-Based Active Memory and Self-AttentionCode0
Homonymy Information for English WordNetCode0
Error Analysis of using BART for Multi-Document Summarization: A Study for English and German LanguageCode0
Improving Context Aware Language ModelsCode0
Aligning Language Models to Explicitly Handle AmbiguityCode0
GeneMask: Fast Pretraining of Gene Sequences to Enable Few-Shot LearningCode0
Error Detection for Text-to-SQL Semantic ParsingCode0
A Novel Approach for Automatic Program Repair using Round-Trip Translation with Large Language ModelsCode0
Indic-Transformers: An Analysis of Transformer Language Models for Indian LanguagesCode0
Error-preserving Automatic Speech Recognition of Young English Learners' LanguageCode0
Honey, I Shrunk the Language: Language Model Behavior at Reduced ScaleCode0
A Note on Learning Rare Events in Molecular Dynamics using LSTM and TransformerCode0
CroissantLLM: A Truly Bilingual French-English Language ModelCode0
Critic-Driven Decoding for Mitigating Hallucinations in Data-to-text GenerationCode0
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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