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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 6001–6050 of 17610 papers

TitleStatusHype
RAG-based Question Answering over Heterogeneous Data and Text—0
DiffSensei: Bridging Multi-Modal LLMs and Diffusion Models for Customized Manga Generation—0
IntellectSeeker: A Personalized Literature Management System with the Probabilistic Model and Large Language ModelCode0
CoPrUS: Consistency Preserving Utterance Synthesis towards more realistic benchmark dialoguesCode0
Active Inference for Self-Organizing Multi-LLM Systems: A Bayesian Thermodynamic Approach to AdaptationCode0
Agents for self-driving laboratories applied to quantum computing—0
Filling Memory Gaps: Enhancing Continual Semantic Parsing via SQL Syntax Variance-Guided LLMs without Real Data Replay—0
Breaking the Stage Barrier: A Novel Single-Stage Approach to Long Context Extension for Large Language Models—0
Automatic Item Generation for Personality Situational Judgment Tests with Large Language Models—0
ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance—0
Exploring Critical Testing Scenarios for Decision-Making Policies: An LLM Approach—0
Effective Text Adaptation for LLM-based ASR through Soft Prompt Fine-Tuning—0
Small Languages, Big Models: A Study of Continual Training on Languages of Norway—0
LINKs: Large Language Model Integrated Management for 6G Empowered Digital Twin NetworKs—0
Simulating Human-like Daily Activities with Desire-driven Autonomy—0
MAVias: Mitigate any Visual Bias—0
OmniEvalKit: A Modular, Lightweight Toolbox for Evaluating Large Language Model and its Omni-Extensions—0
Leveraging Prompt Learning and Pause Encoding for Alzheimer's Disease Detection—0
Unseen Attack Detection in Software-Defined Networking Using a BERT-Based Large Language Model—0
Enhanced Computationally Efficient Long LoRA Inspired Perceiver Architectures for Auto-Regressive Language Modeling—0
GL-Fusion: Rethinking the Combination of Graph Neural Network and Large Language model—0
Cooperative SQL Generation for Segmented Databases By Using Multi-functional LLM Agents—0
Trust No AI: Prompt Injection Along The CIA Security Triad—0
LVP-CLIP:Revisiting CLIP for Continual Learning with Label Vector Pool—0
Pre-trained protein language model for codon optimization—0
ULMRec: User-centric Large Language Model for Sequential Recommendation—0
SMI-Editor: Edit-based SMILES Language Model with Fragment-level Supervision—0
Confidence Diagram of Nonparametric Ranking for Uncertainty Assessment in Large Language Models Evaluation—0
Text-to-3D Gaussian Splatting with Physics-Grounded Motion Generation—0
PETapter: Leveraging PET-style classification heads for modular few-shot parameter-efficient fine-tuning—0
KaLM: Knowledge-aligned Autoregressive Language Modeling via Dual-view Knowledge Graph Contrastive Learning—0
QueEn: A Large Language Model for Quechua-English Translation—0
Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report GenerationCode0
Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Training—0
Espresso: High Compression For Rich Extraction From Videos for Your Vision-Language Model—0
Generative Humanization for Therapeutic Antibodies—0
Flash Communication: Reducing Tensor Parallelization Bottleneck for Fast Large Language Model Inference—0
CigTime: Corrective Instruction Generation Through Inverse Motion Editing—0
A Survey of Large Language Model-Based Generative AI for Text-to-SQL: Benchmarks, Applications, Use Cases, and Challenges—0
Enhancing Cross-Language Code Translation via Task-Specific Embedding Alignment in Retrieval-Augmented Generation—0
Enhancing LLMs for Impression Generation in Radiology Reports through a Multi-Agent System—0
A Practical Examination of AI-Generated Text Detectors for Large Language Models—0
Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora—0
Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling—0
From Voice to Value: Leveraging AI to Enhance Spoken Online Reviews on the Go—0
Code-as-Monitor: Constraint-aware Visual Programming for Reactive and Proactive Robotic Failure Detection—0
A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios—0
EditScout: Locating Forged Regions from Diffusion-based Edited Images with Multimodal LLM—0
A large language model-type architecture for high-dimensional molecular potential energy surfaces—0
AL-QASIDA: Analyzing LLM Quality and Accuracy Systematically in Dialectal Arabic—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