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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 9801–9850 of 17610 papers

TitleStatusHype
Large Language Model (LLM) Bias Index -- LLMBI—0
Parameter Efficient Tuning Allows Scalable Personalization of LLMs for Text Entry: A Case Study on Abbreviation Expansion—0
Speech Translation with Large Language Models: An Industrial Practice—0
LiDAR-LLM: Exploring the Potential of Large Language Models for 3D LiDAR Understanding—0
Shai: A large language model for asset management—0
Carve3D: Improving Multi-view Reconstruction Consistency for Diffusion Models with RL Finetuning—0
Developing Interactive Tourism Planning: A Dialogue Robot System Powered by a Large Language Model—0
Multi-Sentence Grounding for Long-term Instructional Video—0
Exploiting Contextual Target Attributes for Target Sentiment Classification—0
How to Prune Your Language Model: Recovering Accuracy on the "Sparsity May Cry'' Benchmark—0
AsyncMLD: Asynchronous Multi-LLM Framework for Dialogue Recommendation System—0
VideoPoet: A Large Language Model for Zero-Shot Video Generation—0
LlaMaVAE: Guiding Large Language Model Generation via Continuous Latent Sentence Spaces—0
Language Resources for Dutch Large Language Modelling—0
MonoCoder: Domain-Specific Code Language Model for HPC Codes and TasksCode0
AMD:Anatomical Motion Diffusion with Interpretable Motion Decomposition and Fusion—0
ALMANACS: A Simulatability Benchmark for Language Model ExplainabilityCode0
HCDIR: End-to-end Hate Context Detection, and Intensity Reduction model for online comments—0
In Generative AI we Trust: Can Chatbots Effectively Verify Political Information?—0
dIR -- Discrete Information Retrieval: Conversational Search over Unstructured (and Structured) Data with Large Language Models—0
DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines—0
Dynamic Topic Language Model on Heterogeneous Children's Mental Health Clinical Notes—0
External Knowledge Augmented Polyphone Disambiguation Using Large Language Model—0
A Performance Evaluation of a Quantized Large Language Model on Various Smartphones—0
CrossBind: Collaborative Cross-Modal Identification of Protein Nucleic-Acid-Binding ResiduesCode0
IPAD: Iterative, Parallel, and Diffusion-based Network for Scene Text RecognitionCode0
Difficulty-Focused Contrastive Learning for Knowledge Tracing with a Large Language Model-Based Difficulty Prediction—0
Can ChatGPT be Your Personal Medical Assistant?—0
Founder-GPT: Self-play to evaluate the Founder-Idea fit—0
PEPT: Expert Finding Meets Personalized Pre-training—0
Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives—0
Jack of All Tasks, Master of Many: Designing General-purpose Coarse-to-Fine Vision-Language Model—0
Text-Conditioned Resampler For Long Form Video Understanding—0
Linear Attention via Orthogonal Memory—0
Understanding the Multi-modal Prompts of the Pre-trained Vision-Language Model—0
Robust Stochastic Graph Generator for Counterfactual Explanations—0
UniDCP: Unifying Multiple Medical Vision-language Tasks via Dynamic Cross-modal Learnable Prompts—0
VinaLLaMA: LLaMA-based Vietnamese Foundation Model—0
Evaluating Language-Model Agents on Realistic Autonomous Tasks—0
Indoor and Outdoor 3D Scene Graph Generation via Language-Enabled Spatial Ontologies—0
Entity or Relation Embeddings? An Analysis of Encoding Strategies for Relation ExtractionCode0
FedMKGC: Privacy-Preserving Federated Multilingual Knowledge Graph Completion—0
Decoding Concerns: Multi-label Classification of Vaccine Sentiments in Social MediaCode0
Demystifying Instruction Mixing for Fine-tuning Large Language ModelsCode0
LLM-Twin: Mini-Giant Model-driven Beyond 5G Digital Twin Networking Framework with Semantic Secure Communication and Computation—0
Towards Efficient Vision-Language Tuning: More Information Density, More Generalizability—0
Pedestrian Attribute Recognition via CLIP based Prompt Vision-Language Fusion—0
Mixed Distillation Helps Smaller Language Model Better Reasoning—0
Knowledge Trees: Gradient Boosting Decision Trees on Knowledge Neurons as Probing Classifier—0
Paloma: A Benchmark for Evaluating Language Model Fit—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