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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 19011950 of 17610 papers

TitleStatusHype
Enhancing Multilingual Language Model with Massive Multilingual Knowledge TriplesCode1
Federated Learning for ASR based on Wav2vec 2.0Code1
Fast Vocabulary Transfer for Language Model CompressionCode1
FATA-Trans: Field And Time-Aware Transformer for Sequential Tabular DataCode1
Analysing Discrete Self Supervised Speech Representation for Spoken Language ModelingCode1
FastRE: Towards Fast Relation Extraction with Convolutional Encoder and Improved Cascade Binary Tagging FrameworkCode1
Analysing Lexical Semantic Change with Contextualised Word RepresentationsCode1
Knowledge Graph-Driven Retrieval-Augmented Generation: Integrating Deepseek-R1 with Weaviate for Advanced Chatbot ApplicationsCode1
Fauno: The Italian Large Language Model that will leave you senza parole!Code1
Knowledge Graphs and Pre-trained Language Models enhanced Representation Learning for Conversational Recommender SystemsCode1
Autonomous Microscopy Experiments through Large Language Model AgentsCode1
AutoProteinEngine: A Large Language Model Driven Agent Framework for Multimodal AutoML in Protein EngineeringCode1
Analysing The Impact of Sequence Composition on Language Model Pre-TrainingCode1
Fast Model Editing at ScaleCode1
A Study of Generative Large Language Model for Medical Research and HealthcareCode1
KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation ExtractionCode1
Knowledge Unlearning for Mitigating Privacy Risks in Language ModelsCode1
KnowMAN: Weakly Supervised Multinomial Adversarial NetworksCode1
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary CellsCode1
A Large Language Model Enhanced Sequential Recommender for Joint Video and Comment RecommendationCode1
BERT is to NLP what AlexNet is to CV: Can Pre-Trained Language Models Identify Analogies?Code1
Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-TaskLearning for Offensive Language DetectionCode1
BERTScore is Unfair: On Social Bias in Language Model-Based Metrics for Text GenerationCode1
AutoScale: Scale-Aware Data Mixing for Pre-Training LLMsCode1
AutoScrum: Automating Project Planning Using Large Language ModelsCode1
L3Cube-HingCorpus and HingBERT: A Code Mixed Hindi-English Dataset and BERT Language ModelsCode1
Faster Causal Attention Over Large Sequences Through Sparse Flash AttentionCode1
LaCo: Large Language Model Pruning via Layer CollapseCode1
Fast-R2D2: A Pretrained Recursive Neural Network based on Pruned CKY for Grammar Induction and Text RepresentationCode1
Few-Shot Detection of Machine-Generated Text using Style RepresentationsCode1
Fine-tuning Large Language Models for Adaptive Machine TranslationCode1
GLADIS: A General and Large Acronym Disambiguation BenchmarkCode1
LAMP: Leveraging Language Prompts for Multi-person Pose EstimationCode1
Improving antibody language models with native pairingCode1
Large language model validity via enhanced conformal prediction methodsCode1
Factual Probing Is [MASK]: Learning vs. Learning to RecallCode1
Language-agnostic BERT Sentence EmbeddingCode1
Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven ExplorationCode1
ADEPT: A DEbiasing PrompT FrameworkCode1
LADDER: Language Driven Slice Discovery and Error RectificationCode1
Language Generation from Brain RecordingsCode1
Language Generation with Strictly Proper Scoring RulesCode1
FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language ModelCode1
Factorized Learning Assisted with Large Language Model for Gloss-free Sign Language TranslationCode1
AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language ModelsCode1
Factorized Neural Transducer for Efficient Language Model AdaptationCode1
Avoiding Inference Heuristics in Few-shot Prompt-based FinetuningCode1
Language Model Decomposition: Quantifying the Dependency and Correlation of Language ModelsCode1
Fairer Preferences Elicit Improved Human-Aligned Large Language Model JudgmentsCode1
Extracting Training Data from Large Language ModelsCode1
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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