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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 7701–7750 of 17610 papers

TitleStatusHype
HerBERT: Efficiently Pretrained Transformer-based Language Model for Polish—0
Hermes: A Large Language Model Framework on the Journey to Autonomous Networks—0
HeRo: RoBERTa and Longformer Hebrew Language Models—0
Heterogeneous Federated Learning Using Knowledge Codistillation—0
Heterogeneous Knowledge Fusion: A Novel Approach for Personalized Recommendation via LLM—0
Heterogeneous Language Model Optimization in Automatic Speech Recognition—0
HeteroLLM: Accelerating Large Language Model Inference on Mobile SoCs platform with Heterogeneous AI Accelerators—0
HeGTa: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding—0
Hierarchical Continual Reinforcement Learning via Large Language Model—0
Hidden Persuasion: Detecting Manipulative Narratives on Social Media During the 2022 Russian Invasion of Ukraine—0
Hidden Schema Networks—0
Hidden State Variability of Pretrained Language Models Can Guide Computation Reduction for Transfer Learning—0
Hidden You Malicious Goal Into Benign Narratives: Jailbreak Large Language Models through Logic Chain Injection—0
HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model—0
Hide Your Malicious Goal Into Benign Narratives: Jailbreak Large Language Models through Carrier Articles—0
Hierarchical Alignment Decomposition Labels for Hiero Grammar Rules—0
Hierarchical Autoregressive Transformers: Combining Byte- and Word-Level Processing for Robust, Adaptable Language Models—0
Hierarchical Autoscaling for Large Language Model Serving with Chiron—0
Hierarchical Bayesian Language Modelling for the Linguistically Informed—0
Hierarchical Character Tagger for Short Text Spelling Error Correction—0
Hierarchical Classification of Transversal Skills in Job Ads Based on Sentence Embeddings—0
Hierarchical Cross-Modality Knowledge Transfer with Sinkhorn Attention for CTC-based ASR—0
Hierarchical Debate-Based Large Language Model (LLM) for Complex Task Planning of 6G Network Management—0
Hierarchical GPT with Congruent Transformers for Multi-Sentence Language Models—0
Hierarchical Knowledge Graph Construction from Images for Scalable E-Commerce—0
Hierarchical Language Models for Semantic Navigation and Manipulation in an Aerial-Ground Robotic System—0
Hierarchical Latent Words Language Models for Robust Modeling to Out-Of Domain Tasks—0
Hierarchical Level-Wise News Article Clustering via Multilingual Matryoshka Embeddings—0
Hierarchical LSTMs with Adaptive Attention for Visual Captioning—0
Hierarchical LSTM with Adjusted Temporal Attention for Video Captioning—0
Hierarchically-Structured Open-Vocabulary Indoor Scene Synthesis with Pre-trained Large Language Model—0
Hierarchical Multitask Learning Approach for BERT—0
Hierarchical Multi Task Learning With CTC—0
Hierarchical Recurrent Neural Network for Document Modeling—0
Hierarchical Re-ranker Retriever (HRR)—0
Hierarchical Statistical Semantic Realization for Minimal Recursion Semantics—0
Hierarchical Transformer-based Large-Context End-to-end ASR with Large-Context Knowledge Distillation—0
Hierarchical Transformers Are More Efficient Language Models—0
Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Model—0
HierLLM: Hierarchical Large Language Model for Question Recommendation—0
Hi-Gen: Generative Retrieval For Large-Scale Personalized E-commerce Search—0
HiGen: Hierarchy-Aware Sequence Generation for Hierarchical Text Classification—0
High-entropy Advantage in Neural Networks' Generalizability—0
Higher-Order Binding of Language Model Virtual Personas: a Study on Approximating Political Partisan Misperceptions—0
Higher Order Recurrent Neural Networks—0
High Fidelity Text-to-Speech Via Discrete Tokens Using Token Transducer and Group Masked Language Model—0
High fitness paths can connect proteins with low sequence overlap—0
High Order Reasoning for Time Critical Recommendation in Evidence-based Medicine—0
High-performance automated abstract screening with large language model ensembles—0
High Throughput Phenotyping of Physician Notes with Large Language and Hybrid NLP Models—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