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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 26512700 of 17610 papers

TitleStatusHype
LEARN: Knowledge Adaptation from Large Language Model to Recommendation for Practical Industrial ApplicationCode1
Does Your Vision-Language Model Get Lost in the Long Video Sampling Dilemma?Code1
Cascaded Head-colliding AttentionCode1
AraGPT2: Pre-Trained Transformer for Arabic Language GenerationCode1
Knowledge Distillation for BERT Unsupervised Domain AdaptationCode1
CPT: Efficient Deep Neural Network Training via Cyclic PrecisionCode1
Cascade Speculative Drafting for Even Faster LLM InferenceCode1
DomURLs_BERT: Pre-trained BERT-based Model for Malicious Domains and URLs Detection and ClassificationCode1
AgroGPT: Efficient Agricultural Vision-Language Model with Expert TuningCode1
Domain-Aware Dialogue State Tracker for Multi-Domain Dialogue SystemsCode1
Bootstrapping Interactive Image-Text Alignment for Remote Sensing Image CaptioningCode1
Dolphins: Multimodal Language Model for DrivingCode1
CPM: A Large-scale Generative Chinese Pre-trained Language ModelCode1
CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and GenerationCode1
KITLM: Domain-Specific Knowledge InTegration into Language Models for Question AnsweringCode1
Lexi: Self-Supervised Learning of the UI LanguageCode1
CoVR-2: Automatic Data Construction for Composed Video RetrievalCode1
DOMINO: A Dual-System for Multi-step Visual Language ReasoningCode1
KGLM: Integrating Knowledge Graph Structure in Language Models for Link PredictionCode1
Crafting Large Language Models for Enhanced InterpretabilityCode1
CPLLM: Clinical Prediction with Large Language ModelsCode1
Picard understanding Darmok: A Dataset and Model for Metaphor-Rich Translation in a Constructed LanguageCode1
KinyaBERT: a Morphology-aware Kinyarwanda Language ModelCode1
Catwalk: A Unified Language Model Evaluation Framework for Many DatasetsCode1
KM-BART: Knowledge Enhanced Multimodal BART for Visual Commonsense GenerationCode1
Causal Discovery with Language Models as Imperfect ExpertsCode1
Knowledge Distillation from BERT Transformer to Speech Transformer for Intent ClassificationCode1
Knowledge Unlearning for Mitigating Privacy Risks in Language ModelsCode1
LAMP: Extracting Text from Gradients with Language Model PriorsCode1
Causal Effects of Linguistic PropertiesCode1
Keeping it Simple: Language Models can learn Complex Molecular DistributionsCode1
Counterfactual Data Augmentation for Neural Machine TranslationCode1
Cost-effective Instruction Learning for Pathology Vision and Language AnalysisCode1
KELM: Knowledge Enhanced Pre-Trained Language Representations with Message Passing on Hierarchical Relational GraphsCode1
cosFormer: Rethinking Softmax in AttentionCode1
Causal Language Modeling Can Elicit Search and Reasoning Capabilities on Logic PuzzlesCode1
CoSafe: Evaluating Large Language Model Safety in Multi-Turn Dialogue CoreferenceCode1
A Comparison of Methods for OOV-word Recognition on a New Public DatasetCode1
CoS: Enhancing Personalization and Mitigating Bias with Context SteeringCode1
Keep CALM and Explore: Language Models for Action Generation in Text-based GamesCode1
Matrix Information Theory for Self-Supervised LearningCode1
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared RandomnessCode1
KALA: Knowledge-Augmented Language Model AdaptationCode1
DRG-LLaMA : Tuning LLaMA Model to Predict Diagnosis-related Group for Hospitalized PatientsCode1
Coherence boosting: When your pretrained language model is not paying enough attentionCode1
CORBA: Contagious Recursive Blocking Attacks on Multi-Agent Systems Based on Large Language ModelsCode1
CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question AnsweringCode1
Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model InfillingCode1
Kalman Filter Enhanced GRPO for Reinforcement Learning-Based Language Model ReasoningCode1
CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model GenerationCode1
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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