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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 4701–4750 of 17610 papers

TitleStatusHype
MoxE: Mixture of xLSTM Experts with Entropy-Aware Routing for Efficient Language Modeling—0
KoACD: The First Korean Adolescent Dataset for Cognitive Distortion Analysis—0
Red Teaming Large Language Models for Healthcare—0
Patchwork: A Unified Framework for RAG Serving—0
Optimizing Deep Neural Networks using Safety-Guided Self CompressionCode0
Sadeed: Advancing Arabic Diacritization Through Small Language Model—0
Polysemy of Synthetic Neurons Towards a New Type of Explanatory Categorical Vector Spaces—0
Does the Prompt-based Large Language Model Recognize Students' Demographics and Introduce Bias in Essay Scoring?—0
Confidence in Large Language Model Evaluation: A Bayesian Approach to Limited-Sample Challenges—0
Vision-Language Model-Based Semantic-Guided Imaging Biomarker for Early Lung Cancer Detection—0
V3LMA: Visual 3D-enhanced Language Model for Autonomous Driving—0
WenyanGPT: A Large Language Model for Classical Chinese Tasks—0
Universal language model with the intervention of quantum theory—0
UniDetox: Universal Detoxification of Large Language Models via Dataset DistillationCode0
Pretraining Large Brain Language Model for Active BCI: Silent Speech—0
Computational Reasoning of Large Language ModelsCode0
LLM Enhancer: Merged Approach using Vector Embedding for Reducing Large Language Model Hallucinations with External Knowledge—0
LLM-Enabled EV Charging Stations Recommendation—0
Small or Large? Zero-Shot or Finetuned? Guiding Language Model Choice for Specialized Applications in Healthcare—0
MemeBLIP2: A novel lightweight multimodal system to detect harmful memes—0
From Attention to Atoms: Spectral Dictionary Learning for Fast, Interpretable Language Models—0
CoCo-Bench: A Comprehensive Code Benchmark For Multi-task Large Language Model Evaluation—0
A Framework to Assess the Persuasion Risks Large Language Model Chatbots Pose to Democratic Societies—0
BrAIcht, a theatrical agent that speaks like Bertolt Brecht's characters—0
An Automated Reinforcement Learning Reward Design Framework with Large Language Model for Cooperative Platoon Coordination—0
Efficient Domain-adaptive Continual Pretraining for the Process Industry in the German Language—0
CodeBC: A More Secure Large Language Model for Smart Contract Code Generation in BlockchainCode0
Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search—0
GVPO: Group Variance Policy Optimization for Large Language Model Post-Training—0
GenTorrent: Scaling Large Language Model Serving with An Overley Network—0
Unified Multi-Task Learning & Model Fusion for Efficient Language Model Guardrailing—0
Exploring a Large Language Model for Transforming Taxonomic Data into OWL: Lessons Learned and Implications for Ontology Development—0
Improving Language Model Personas via Rationalization with Psychological Scaffolds—0
Fast-Slow Thinking for Large Vision-Language Model Reasoning—0
SMARTFinRAG: Interactive Modularized Financial RAG BenchmarkCode0
The Big Send-off: High Performance Collectives on GPU-based Supercomputers—0
Towards Leveraging Large Language Model Summaries for Topic Modeling in Source Code—0
TimeSoccer: An End-to-End Multimodal Large Language Model for Soccer Commentary Generation—0
Unified Attacks to Large Language Model Watermarks: Spoofing and Scrubbing in Unauthorized Knowledge Distillation—0
Automatically Generating Rules of Malicious Software Packages via Large Language Model—0
FashionM3: Multimodal, Multitask, and Multiround Fashion Assistant based on Unified Vision-Language Model—0
Does Knowledge Distillation Matter for Large Language Model based Bundle Generation?—0
Improving Significant Wave Height Prediction Using Chronos Models—0
In-Context Learning can distort the relationship between sequence likelihoods and biological fitness—0
Planning with Diffusion Models for Target-Oriented Dialogue Systems—0
SplitReason: Learning To Offload Reasoning—0
ParamΔ for Direct Weight Mixing: Post-Train Large Language Model at Zero Cost—0
Target Concrete Score Matching: A Holistic Framework for Discrete Diffusion—0
Monte Carlo Planning with Large Language Model for Text-Based Game Agents—0
Large Language Model Empowered Privacy-Protected Framework for PHI Annotation in Clinical Notes—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