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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 19512000 of 17610 papers

TitleStatusHype
Hydra: A System for Large Multi-Model Deep LearningCode1
Language-Specific Representation of Emotion-Concept Knowledge Causally Supports Emotion InferenceCode1
Automatic Detection of Generated Text is Easiest when Humans are FooledCode1
Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate SpeechCode1
ADIFF: Explaining audio difference using natural languageCode1
Elastic Weight Removal for Faithful and Abstractive Dialogue GenerationCode1
ELECTRAMed: a new pre-trained language representation model for biomedical NLPCode1
Large Language Models as Zero-Shot Keyphrase Extractors: A Preliminary Empirical StudyCode1
ELI5: Long Form Question AnsweringCode1
Elephants Never Forget: Testing Language Models for Memorization of Tabular DataCode1
HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden UnitsCode1
Cross-model Control: Improving Multiple Large Language Models in One-time TrainingCode1
Human Language ModelingCode1
Cross-domain Retrieval in the Legal and Patent Domains: a Reproducibility StudyCode1
Analyzing the Generalization and Reliability of Steering VectorsCode1
A Study of Generative Large Language Model for Medical Research and HealthcareCode1
Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model BiasCode1
Accurate identification of bacteriophages from metagenomic data using TransformerCode1
KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation ExtractionCode1
CDLM: Cross-Document Language ModelingCode1
Distributed Deep Learning in Open CollaborationsCode1
Augmenting Interpretable Models with LLMs during TrainingCode1
Cross-Align: Modeling Deep Cross-lingual Interactions for Word AlignmentCode1
Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News ArticlesCode1
A Large Language Model Enhanced Sequential Recommender for Joint Video and Comment RecommendationCode1
UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language ModelingCode1
Accurate Prediction of Antibody Function and Structure Using Bio-Inspired Antibody Language ModelCode1
Emergent Symbolic Mechanisms Support Abstract Reasoning in Large Language ModelsCode1
Backpack Language ModelsCode1
EMMA: Efficient Visual Alignment in Multi-Modal LLMsCode1
EmoCLIP: A Vision-Language Method for Zero-Shot Video Facial Expression RecognitionCode1
Cross-Platform Video Person ReID: A New Benchmark Dataset and Adaptation ApproachCode1
Identifying the Risks of LM Agents with an LM-Emulated SandboxCode1
Improved training of end-to-end attention models for speech recognitionCode1
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuningCode1
LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language ModelCode1
Unifying Segment Anything in Microscopy with Multimodal Large Language ModelCode1
Empowering Large Language Model for Continual Video Question Answering with Collaborative PromptingCode1
Knowledge-Augmented Language Model VerificationCode1
Empower Entity Set Expansion via Language Model ProbingCode1
Learning Sparse Prototypes for Text GenerationCode1
CREAM: Consistency Regularized Self-Rewarding Language ModelsCode1
Creative Agents: Empowering Agents with Imagination for Creative TasksCode1
How to Fine-Tune BERT for Text Classification?Code1
Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product OperatorsCode1
How Much Knowledge Can You Pack Into the Parameters of a Language Model?Code1
Emulated Disalignment: Safety Alignment for Large Language Models May Backfire!Code1
Balanced Data Sampling for Language Model Training with ClusteringCode1
AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language ModelsCode1
How multilingual is Multilingual BERT?Code1
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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