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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 2001–2050 of 17610 papers

TitleStatusHype
Lifelong Learning of Large Language Model based Agents: A RoadmapCode3
Integrating Pause Information with Word Embeddings in Language Models for Alzheimer's Disease Detection from Spontaneous Speech—0
Modeling Neural Networks with Privacy Using Neural Stochastic Differential Equations—0
Better Prompt Compression Without Multi-Layer Perceptrons—0
GeoPix: Multi-Modal Large Language Model for Pixel-level Image Understanding in Remote Sensing—0
A Study on Educational Data Analysis and Personalized Feedback Report Generation Based on Tags and ChatGPT—0
Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving—0
An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering—0
HeteroLLM: Accelerating Large Language Model Inference on Mobile SoCs platform with Heterogeneous AI Accelerators—0
The Magnitude of Categories of Texts Enriched by Language Models—0
Scaling Down Semantic Leakage: Investigating Associative Bias in Smaller Language ModelsCode0
VASparse: Towards Efficient Visual Hallucination Mitigation for Large Vision-Language Model via Visual-Aware SparsificationCode1
AlgoPilot: Fully Autonomous Program Synthesis Without Human-Written Programs—0
ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code GenerationCode2
Tensor Product Attention Is All You NeedCode0
Environmental large language model Evaluation (ELLE) dataset: A Benchmark for Evaluating Generative AI applications in Eco-environment DomainCode0
Personalized Language Model Learning on Text Data Without User IdentifiersCode0
Large Language Models for Bioinformatics—0
Towards a Probabilistic Framework for Analyzing and Improving LLM-Enabled Software—0
Automating Date Format Detection for Data Visualization—0
Synergizing Large Language Models and Task-specific Models for Time Series Anomaly Detection—0
Scalable Vision Language Model Training via High Quality Data Curation—0
Valley2: Exploring Multimodal Models with Scalable Vision-Language DesignCode3
Linguistic Entity Masking to Improve Cross-Lingual Representation of Multilingual Language Models for Low-Resource Languages—0
Effective faking of verbal deception detection with target-aligned adversarial attacks—0
Contextual ASR Error Handling with LLMs Augmentation for Goal-Oriented Conversational AI—0
Gender-Neutral Large Language Models for Medical Applications: Reducing Bias in PubMed Abstracts—0
MARS6: A Small and Robust Hierarchical-Codec Text-to-Speech Model—0
MinMo: A Multimodal Large Language Model for Seamless Voice Interaction—0
Merging Feed-Forward Sublayers for Compressed TransformersCode1
Centurio: On Drivers of Multilingual Ability of Large Vision-Language ModelCode0
A Text-Based Knowledge-Embedded Soft Sensing Modeling Approach for General Industrial Process Tasks Based on Large Language Model—0
Using LLMs to Infer Non-Binary COVID-19 Sentiments of Chinese Micro-bloggers—0
UAV-VLA: Vision-Language-Action System for Large Scale Aerial Mission GenerationCode2
JELLY: Joint Emotion Recognition and Context Reasoning with LLMs for Conversational Speech Synthesis—0
TreeKV: Smooth Key-Value Cache Compression with Tree Structures—0
LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding—0
Optimizing Estonian TV Subtitles with Semi-supervised Learning and LLMs—0
End-to-End Bangla AI for Solving Math Olympiad Problem Benchmark: Leveraging Large Language Model Using Integrated Approach—0
Robotic Programmer: Video Instructed Policy Code Generation for Robotic Manipulation—0
OpenOmni: Large Language Models Pivot Zero-shot Omnimodal Alignment across Language with Real-time Self-Aware Emotional Speech SynthesisCode2
Scaling Large Language Model Training on Frontier with Low-Bandwidth Partitioning—0
Integrating remote sensing data assimilation, deep learning and large language model for interactive wheat breeding yield prediction—0
AI-Driven Reinvention of Hydrological Modeling for Accurate Predictions and Interpretation to Transform Earth System Modeling—0
BabyLMs for isiXhosa: Data-Efficient Language Modelling in a Low-Resource Context—0
CL3DOR: Contrastive Learning for 3D Large Multimodal Models via Odds Ratio on High-Resolution Point Clouds—0
Sa2VA: Marrying SAM2 with LLaVA for Dense Grounded Understanding of Images and VideosCode5
Self-adaptive vision-language model for 3D segmentation of pulmonary artery and vein—0
Investigating the Impact of Data Selection Strategies on Language Model PerformanceCode0
Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case StudyCode0
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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