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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 8401–8450 of 17610 papers

TitleStatusHype
ExplainableDetector: Exploring Transformer-based Language Modeling Approach for SMS Spam Detection with Explainability Analysis—0
Post Training Quantization of Large Language Models with Microscaling Formats—0
DiffGen: Robot Demonstration Generation via Differentiable Physics Simulation, Differentiable Rendering, and Vision-Language Model—0
Advanced Natural-based interaction for the ITAlian language: LLaMAntino-3-ANITA—0
Large Language Model-aided Edge Learning in Distribution System State Estimation—0
Quite Good, but Not Enough: Nationality Bias in Large Language Models -- A Case Study of ChatGPTCode0
LMD3: Language Model Data Density Dependence—0
SaudiBERT: A Large Language Model Pretrained on Saudi Dialect CorporaCode0
Large Language Model in Financial Regulatory Interpretation—0
Improving Targeted Molecule Generation through Language Model Fine-Tuning Via Reinforcement Learning—0
Correlation Dimension of Natural Language in a Statistical Manifold—0
Improving Instruction Following in Language Models through Proxy-Based Uncertainty EstimationCode0
E2TP: Element to Tuple Prompting Improves Aspect Sentiment Tuple PredictionCode0
CANAL -- Cyber Activity News Alerting Language Model: Empirical Approach vs. Expensive LLM—0
Boosting Large Language Models with Continual Learning for Aspect-based Sentiment Analysis—0
Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?—0
Parameter-Efficient Fine-Tuning With Adapters—0
Similarity Guided Multimodal Fusion Transformer for Semantic Location Prediction in Social Media—0
Towards a More Inclusive AI: Progress and Perspectives in Large Language Model Training for the Sámi Language—0
Large Language Model-Aided Evolutionary Search for Constrained Multiobjective Optimization—0
Towards a Path Dependent Account of Category FluencyCode0
Vision-Language Modeling with Regularized Spatial Transformer Networks for All Weather Crosswind Landing of Aircraft—0
XAMPLER: Learning to Retrieve Cross-Lingual In-Context ExamplesCode0
Information Extraction from Historical Well Records Using A Large Language Model—0
CourseGPT-zh: an Educational Large Language Model Based on Knowledge Distillation Incorporating Prompt Optimization—0
ChuXin: 1.6B Technical Report—0
Encoder-Decoder Framework for Interactive Free Verses with Generation with Controllable High-Quality Rhyming—0
Impact of Tone-Aware Explanations in Recommender Systems—0
Conversational Topic Recommendation in Counseling and Psychotherapy with Decision Transformer and Large Language Models—0
Chain of Thoughtlessness? An Analysis of CoT in Planning—0
BiasKG: Adversarial Knowledge Graphs to Induce Bias in Large Language ModelsCode0
AirGapAgent: Protecting Privacy-Conscious Conversational Agents—0
LOC-ZSON: Language-driven Object-Centric Zero-Shot Object Retrieval and Navigation—0
KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation—0
Large Language Model Enhanced Machine Learning Estimators for ClassificationCode0
QFMTS: Generating Query-Focused Summaries over Multi-Table Inputs—0
KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization—0
Representation Learning of Daily Movement Data Using Text EncodersCode0
SUTRA: Scalable Multilingual Language Model Architecture—0
Language Modeling Using Tensor TrainsCode0
Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScore—0
FlashBack:Efficient Retrieval-Augmented Language Modeling for Long Context Inference—0
DrugLLM: Open Large Language Model for Few-shot Molecule Generation—0
A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI—0
Enhancing Knowledge Retrieval with Topic Modeling for Knowledge-Grounded DialogueCode0
Deception in Reinforced Autonomous Agents—0
A Transformer with Stack AttentionCode0
ChatHuman: Language-driven 3D Human Understanding with Retrieval-Augmented Tool Reasoning—0
Enhancing Q-Learning with Large Language Model Heuristics—0
ID-centric Pre-training for Recommendation—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