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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

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Showing 8651–8700 of 17610 papers

TitleStatusHype
Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification—0
Knowledge-augmented Few-shot Visual Relation Detection—0
Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering—0
Knowledge-aware Alert Aggregation in Large-scale Cloud Systems: a Hybrid Approach—0
Knowledge-Aware Conversational Semantic Parsing Over Web Tables—0
Knowledge-Aware Language Model Pretraining—0
Knowledge-based Query Expansion in Real-Time Microblog Search—0
Knowledge Distillation-Empowered Digital Twin for Anomaly Detection—0
Knowledge Distillation for Improved Accuracy in Spoken Question Answering—0
Knowledge Distillation for Neural Transducers from Large Self-Supervised Pre-trained Models—0
Knowledge Distillation For Recurrent Neural Network Language Modeling With Trust Regularization—0
Knowledge distillation from language model to acoustic model: a hierarchical multi-task learning approach—0
Knowledge Distillation from Language-Oriented to Emergent Communication for Multi-Agent Remote Control—0
Knowledge Distillation of Transformer-based Language Models Revisited—0
Knowledge Distillation vs. Pretraining from Scratch under a Fixed (Computation) Budget—0
Knowledge Distillation with Training Wheels—0
Knowledge-driven Encode, Retrieve, Paraphrase for Medical Image Report Generation—0
Knowledge Editing for Large Language Model with Knowledge Neuronal Ensemble—0
Knowledge Efficient Deep Learning for Natural Language Processing—0
Knowledge-enhanced Agents for Interactive Text Games—0
EA-KD: Entropy-based Adaptive Knowledge Distillation—0
Knowledge Graph Enhanced Large Language Model Editing—0
Knowledge Graph Fusion for Language Model Fine-tuning—0
Knowledge Graph Guided Semantic Evaluation of Language Models For User Trust—0
Knowledge Graph Large Language Model (KG-LLM) for Link Prediction—0
Knowledge Graph Modeling-Driven Large Language Model Operating System (LLM OS) for Task Automation in Process Engineering Problem-Solving—0
Knowledge Graphs Construction from Criminal Court Appeals: Insights from the French Cassation Court—0
Knowledge Graph Tuning: Real-time Large Language Model Personalization based on Human Feedback—0
Knowledge-grounded Adaptation Strategy for Vision-language Models: Building Unique Case-set for Screening Mammograms for Residents Training—0
Knowledge-Grounded Dialogue Generation with a Unified Knowledge Representation—0
Knowledge-Grounded Dialogue Generation with a Unified Knowledge Representation—0
Knowledge Guided Encoder-Decoder Framework: Integrating Multiple Physical Models for Agricultural Ecosystem Modeling—0
Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models—0
Knowledge-Infused Legal Wisdom: Navigating LLM Consultation through the Lens of Diagnostics and Positive-Unlabeled Reinforcement Learning—0
Knowledge-Infused Self Attention Transformers—0
KnowledgeNavigator: Leveraging Large Language Models for Enhanced Reasoning over Knowledge Graph—0
Knowledge Overshadowing Causes Amalgamated Hallucination in Large Language Models—0
Knowledge Prompting for Few-shot Action Recognition—0
Knowledge-Rich Morphological Priors for Bayesian Language Models—0
Knowledge Sharing in Manufacturing using Large Language Models: User Evaluation and Model Benchmarking—0
Knowledge Synthesis of Photosynthesis Research Using a Large Language Model—0
Knowledge Tagging with Large Language Model based Multi-Agent System—0
Knowledge Transfer from Large-scale Pretrained Language Models to End-to-end Speech Recognizers—0
Knowledge Transfer with Medical Language Embeddings—0
Knowledge Trees: Gradient Boosting Decision Trees on Knowledge Neurons as Probing Classifier—0
Know "No'' Better: A Data-Driven Approach for Enhancing Negation Awareness in CLIP—0
KnowSemLM: A Knowledge Infused Semantic Language Model—0
Know Thy Judge: On the Robustness Meta-Evaluation of LLM Safety Judges—0
Know Where You're Going: Meta-Learning for Parameter-Efficient Fine-Tuning—0
Know your audience: specializing grounded language models with listener subtraction—0
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All datasetsWikiText-103Penn Treebank (Word Level)enwik8The PileWikiText-2LAMBADAOne Billion WordText8Penn Treebank (Character Level)Hutter PrizeOpenWebTextSALMon

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67—Unverified
2GRUValidation perplexity53.78—Unverified
3LSTMValidation perplexity52.73—Unverified
4LSTMTest perplexity48.7—Unverified
5Temporal CNNTest perplexity45.2—Unverified
6TCNTest perplexity45.19—Unverified
7GCNN-8Test perplexity44.9—Unverified
8Neural cache model (size = 100)Test perplexity44.8—Unverified
9Neural cache model (size = 2,000)Test perplexity40.8—Unverified
10GPT-2 SmallTest perplexity37.5—Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47—Unverified
2Seq-U-NetTest perplexity107.95—Unverified
3GRU (Bai et al., 2018)Test perplexity92.48—Unverified
4R-TransformerTest perplexity84.38—Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7—Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7—Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93—Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4—Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2—Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67—Unverified
2HypernetworksBit per Character (BPC)1.34—Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33—Unverified
4LN HM-LSTMBit per Character (BPC)1.32—Unverified
5ByteNetBit per Character (BPC)1.31—Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27—Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25—Unverified
8Large mLSTMBit per Character (BPC)1.24—Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23—Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22—Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33—Unverified
2OPT 125MTest perplexity32.26—Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1—Unverified
4OPT 1.3BTest perplexity19.55—Unverified
5GPT-Neo 125MTest perplexity17.83—Unverified
6OPT 2.7BTest perplexity17.81—Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12—Unverified
8GPT-Neo 1.3BTest perplexity11.46—Unverified
9Transformer 125MTest perplexity10.7—Unverified
10GPT-Neo 2.7BTest perplexity10.44—Unverified