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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 12101–12150 of 17610 papers

TitleStatusHype
When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1—0
When and why are log-linear models self-normalizing?—0
Unsupervised Inflection Generation Using Neural Language Modeling—0
Zero-Shot Dense Retrieval with Embeddings from Relevance Feedback—0
Zero-Shot Dense Video Captioning by Jointly Optimizing Text and Moment—0
Zipporah: a Fast and Scalable Data Cleaning System for Noisy Web-Crawled Parallel Corpora—0
When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing—0
Zero-shot Entity and Tweet Characterization with Designed Conditional Prompts and Contexts—0
Unified Representation of Genomic and Biomedical Concepts through Multi-Task, Multi-Source Contrastive Learning—0
Zero-shot Generalization in Dialog State Tracking through Generative Question Answering—0
When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications—0
When Does Syntax Mediate Neural Language Model Performance? Evidence from Dropout Probes—0
Zero-shot Generation of Coherent Storybook from Plain Text Story using Diffusion Models—0
Failures to Find Transferable Image Jailbreaks Between Vision-Language Models—0
Zero-shot Hazard Identification in Autonomous Driving: A Case Study on the COOOL Benchmark—0
WHEN FLUE MEETS FLANG: Benchmarks and Large Pre-trained Language Model for Financial Domain—0
Zero-Shot Hierarchical Classification on the Common Procurement Vocabulary Taxonomy—0
Unified Pathological Speech Analysis with Prompt Tuning—0
Unsupervised Human Preference Learning—0
When Large Language Model Agents Meet 6G Networks: Perception, Grounding, and Alignment—0
When Large Language Model Meets Optimization—0
Unsupervised Domain Adaptation of Language Models for Reading Comprehension—0
Mapping Biomedical Ontology Terms to IDs: Effect of Domain Prevalence on Prediction Accuracy—0
SOEN-101: Code Generation by Emulating Software Process Models Using Large Language Model Agents—0
Unsupervised Domain Adaptation in Cross-corpora Abusive Language Detection—0
When More is not Necessary Better: Multilingual Auxiliary Tasks for Zero-Shot Cross-Lingual Transfer of Hate Speech Detection Models—0
When Persuasion Overrides Truth in Multi-Agent LLM Debates: Introducing a Confidence-Weighted Persuasion Override Rate (CW-POR)—0
Unified Multi-Task Learning & Model Fusion for Efficient Language Model Guardrailing—0
When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?—0
When Reasoning Meets Compression: Benchmarking Compressed Large Reasoning Models on Complex Reasoning Tasks—0
When Text Embedding Meets Large Language Model: A Comprehensive Survey—0
Ziya-Visual: Bilingual Large Vision-Language Model via Multi-Task Instruction Tuning—0
Unsupervised Distractor Generation via Large Language Model Distilling and Counterfactual Contrastive Decoding—0
Unsupervised Discovery of Unaccusative and Unergative Verbs—0
Unsupervised Discovery of Linguistic Structure Including Two-level Acoustic Patterns Using Three Cascaded Stages of Iterative Optimization—0
Where exactly does contextualization in a PLM happen?—0
Unified Multimodal Pre-training and Prompt-based Tuning for Vision-Language Understanding and Generation—0
Unsupervised Dependency Graph Network—0
Which Prompts Make The Difference? Data Prioritization For Efficient Human LLM Evaluation—0
Which side are you on? Insider-Outsider classification in conspiracy-theoretic social media—0
Which techniques does your application use?: An information extraction framework for scientific articles—0
Which Words Matter in Defining Phrase Reordering Behavior in Statistical Machine Translation?—0
Unsupervised Data Augmentation for Aspect Based Sentiment Analysis—0
Unsupervised Code-Switching for Multilingual Historical Document Transcription—0
Whisper-GPT: A Hybrid Representation Audio Large Language Model—0
WhisQ: Cross-Modal Representation Learning for Text-to-Music MOS Prediction—0
White Men Lead, Black Women Help? Benchmarking and Mitigating Language Agency Social Biases in LLMs—0
Who Brings the Frisbee: Probing Hidden Hallucination Factors in Large Vision-Language Model via Causality Analysis—0
Zero-shot information extraction from radiological reports using ChatGPT—0
Zero-Shot Learning Based Approach For Medieval Word Recognition Using Deep-Learned Features—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