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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 4751–4800 of 17610 papers

TitleStatusHype
LLMs meet Federated Learning for Scalable and Secure IoT Management—0
Research on Cloud Platform Network Traffic Monitoring and Anomaly Detection System based on Large Language Models—0
Do It For Me vs. Do It With Me: Investigating User Perceptions of Different Paradigms of Automation in Copilots for Feature-Rich Software—0
Benchmarking LLM for Code Smells Detection: OpenAI GPT-4.0 vs DeepSeek-V3—0
FaceInsight: A Multimodal Large Language Model for Face Perception—0
Enhancing TCR-Peptide Interaction Prediction with Pretrained Language Models and Molecular Representations—0
DATETIME: A new benchmark to measure LLM translation and reasoning capabilitiesCode0
What's the Difference? Supporting Users in Identifying the Effects of Prompt and Model Changes Through Token PatternsCode0
Virology Capabilities Test (VCT): A Multimodal Virology Q&A BenchmarkCode0
Values in the Wild: Discovering and Analyzing Values in Real-World Language Model Interactions—0
LAPP: Large Language Model Feedback for Preference-Driven Reinforcement Learning—0
Speculative Sampling via Exponential Races—0
RepliBench: Evaluating the Autonomous Replication Capabilities of Language Model Agents—0
Kuwain 1.5B: An Arabic SLM via Language Injection—0
EasyEdit2: An Easy-to-use Steering Framework for Editing Large Language Models—0
Automatic Text Summarization (ATS) for Research Documents in Sorani Kurdish—0
ResNetVLLM-2: Addressing ResNetVLLM's Multi-Modal Hallucinations—0
OmniV-Med: Scaling Medical Vision-Language Model for Universal Visual Understanding—0
PROMPTEVALS: A Dataset of Assertions and Guardrails for Custom Production Large Language Model Pipelines—0
ResNetVLLM -- Multi-modal Vision LLM for the Video Understanding Task—0
Large Language Model Enhanced Particle Swarm Optimization for Hyperparameter Tuning for Deep Learning Models—0
SOTOPIA-S4: a user-friendly system for flexible, customizable, and large-scale social simulation—0
Improving the Serving Performance of Multi-LoRA Large Language Models via Efficient LoRA and KV Cache Management—0
Bottom-Up Synthesis of Knowledge-Grounded Task-Oriented Dialogues with Iteratively Self-Refined Prompts—0
A Multimodal Recaptioning Framework to Account for Perceptual Diversity in Multilingual Vision-Language Modeling—0
Chain-of-Thought Textual Reasoning for Few-shot Temporal Action Localization—0
A mean teacher algorithm for unlearning of language modelsCode0
Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models—0
A Baseline for Self-state Identification and Classification in Mental Health Data: CLPsych 2025 Task—0
Zero-Shot Industrial Anomaly Segmentation with Image-Aware Prompt GenerationCode0
Large Language Bayes—0
System of Agentic AI for the Discovery of Metal-Organic Frameworks—0
PV-VLM: A Multimodal Vision-Language Approach Incorporating Sky Images for Intra-Hour Photovoltaic Power Forecasting—0
Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving SafetyCode0
RAG Without the Lag: Interactive Debugging for Retrieval-Augmented Generation Pipelines—0
Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep ClassificationCode0
Low-hallucination Synthetic Captions for Large-Scale Vision-Language Model Pre-training—0
It's All Connected: A Journey Through Test-Time Memorization, Attentional Bias, Retention, and Online Optimization—0
Pandora: A Code-Driven Large Language Model Agent for Unified Reasoning Across Diverse Structured Knowledge—0
Sparks of Science: Hypothesis Generation Using Structured Paper Data—0
Are Retrials All You Need? Enhancing Large Language Model Reasoning Without Verbalized Feedback—0
ChatEXAONEPath: An Expert-level Multimodal Large Language Model for Histopathology Using Whole Slide Images—0
DIDS: Domain Impact-aware Data Sampling for Large Language Model Training—0
Energy-Based Reward Models for Robust Language Model AlignmentCode0
CLIMB: CLustering-based Iterative Data Mixture Bootstrapping for Language Model Pre-training—0
VLLFL: A Vision-Language Model Based Lightweight Federated Learning Framework for Smart Agriculture—0
Mixer Metaphors: audio interfaces for non-musical applications—0
Securing the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions—0
Towards Conversational AI for Human-Machine Collaborative MLOps—0
Rethinking LLM-Based Recommendations: A Query Generation-Based, Training-Free Approach—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