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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 4301–4350 of 17610 papers

TitleStatusHype
Preemptive Hallucination Reduction: An Input-Level Approach for Multimodal Language Model—0
Learning Parametric Distributions from Samples and PreferencesCode0
SCORPIO: Serving the Right Requests at the Right Time for Heterogeneous SLOs in LLM Inference—0
Large Language Model Meets Constraint Propagation—0
Position: Federated Foundation Language Model Post-Training Should Focus on Open-Source Models—0
Reducing Latency in LLM-Based Natural Language Commands Processing for Robot Navigation—0
Spoken Language Modeling with Duration-Penalized Self-Supervised UnitsCode0
SeG-SR: Integrating Semantic Knowledge into Remote Sensing Image Super-Resolution via Vision-Language ModelCode0
Understanding the Information Propagation Effects of Communication Topologies in LLM-based Multi-Agent SystemsCode0
Hidden Persuasion: Detecting Manipulative Narratives on Social Media During the 2022 Russian Invasion of Ukraine—0
Critical Batch Size Revisited: A Simple Empirical Approach to Large-Batch Language Model Training—0
Augment or Not? A Comparative Study of Pure and Augmented Large Language Model RecommendersCode0
Actor-Critic based Online Data Mixing For Language Model Pre-Training—0
Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners—0
Discriminative Policy Optimization for Token-Level Reward ModelsCode0
CDR-Agent: Intelligent Selection and Execution of Clinical Decision Rules Using Large Language Model AgentsCode0
Dataset Cartography for Large Language Model Alignment: Mapping and Diagnosing Preference Data—0
Disrupting Vision-Language Model-Driven Navigation Services via Adversarial Object Fusion—0
FLAT-LLM: Fine-grained Low-rank Activation Space Transformation for Large Language Model CompressionCode0
Active Layer-Contrastive Decoding Reduces Hallucination in Large Language Model Generation—0
Diversity-Aware Policy Optimization for Large Language Model Reasoning—0
ATLAS: Learning to Optimally Memorize the Context at Test Time—0
An Empirical Study of Federated Prompt Learning for Vision Language Model—0
Beam-Guided Knowledge Replay for Knowledge-Rich Image Captioning using Vision-Language Model—0
Unsupervised Word-level Quality Estimation for Machine Translation Through the Lens of Annotators (Dis)agreementCode0
VLM-RRT: Vision Language Model Guided RRT Search for Autonomous UAV Navigation—0
VScan: Rethinking Visual Token Reduction for Efficient Large Vision-Language Models—0
Speech as a Multimodal Digital Phenotype for Multi-Task LLM-based Mental Health Prediction—0
NGPU-LM: GPU-Accelerated N-Gram Language Model for Context-Biasing in Greedy ASR Decoding—0
Position: Uncertainty Quantification Needs Reassessment for Large-language Model Agents—0
Operationalizing CaMeL: Strengthening LLM Defenses for Enterprise Deployment—0
LLM-ODDR: A Large Language Model Framework for Joint Order Dispatching and Driver Repositioning—0
GateNLP at SemEval-2025 Task 10: Hierarchical Three-Step Prompting for Multilingual Narrative ClassificationCode0
BugWhisperer: Fine-Tuning LLMs for SoC Hardware Vulnerability Detection—0
CLUE: Neural Networks Calibration via Learning Uncertainty-Error alignment—0
BOFormer: Learning to Solve Multi-Objective Bayesian Optimization via Non-Markovian RL—0
3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model—0
A Tool for Generating Exceptional Behavior Tests With Large Language ModelsCode0
Conversational Alignment with Artificial Intelligence in Context—0
Incorporating LLMs for Large-Scale Urban Complex Mobility Simulation—0
EnsemW2S: Enhancing Weak-to-Strong Generalization with Large Language Model Ensembles—0
ICH-Qwen: A Large Language Model Towards Chinese Intangible Cultural Heritage—0
A Large Language Model-Enabled Control Architecture for Dynamic Resource Capability Exploration in Multi-Agent Manufacturing Systems—0
Improving Brain-to-Image Reconstruction via Fine-Grained Text Bridging—0
Automated Essay Scoring Incorporating Annotations from Automated Feedback Systems—0
Cross-modal RAG: Sub-dimensional Retrieval-Augmented Text-to-Image GenerationCode0
CFP-Gen: Combinatorial Functional Protein Generation via Diffusion Language ModelsCode0
HAD: Hybrid Architecture Distillation Outperforms Teacher in Genomic Sequence Modeling—0
Complex System Diagnostics Using a Knowledge Graph-Informed and Large Language Model-Enhanced Framework—0
Automated Privacy Information Annotation in Large Language Model InteractionsCode0
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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