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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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 7451–7500 of 17610 papers

TitleStatusHype
SRIUBC-Core: Multiword Soft Similarity Models for Textual Similarity—0
SR-LLM: Rethinking the Structured Representation in Large Language Model—0
Unifying Large Language Model and Deep Reinforcement Learning for Human-in-Loop Interactive Socially-aware Navigation—0
SRU++: Pioneering Fast Recurrence with Attention for Speech Recognition—0
SSCAE -- Semantic, Syntactic, and Context-aware natural language Adversarial Examples generator—0
SSN_ARMM@ LT-EDI -ACL2022: Hope Speech Detection for Equality, Diversity, and Inclusion Using ALBERT model—0
SSR: Alignment-Aware Modality Connector for Speech Language Models—0
SSSD: Simply-Scalable Speculative Decoding—0
ST^3: Accelerating Multimodal Large Language Model by Spatial-Temporal Visual Token Trimming—0
Stability Analysis of ChatGPT-based Sentiment Analysis in AI Quality Assurance—0
Stable Code Technical Report—0
Stable Language Model Pre-training by Reducing Embedding Variability—0
StableMask: Refining Causal Masking in Decoder-only Transformer—0
StableMoE: Stable Routing Strategy for Mixture of Experts—0
Stack-and-Delay: a new codebook pattern for music generation—0
Stack-based Multi-layer Attention for Transition-based Dependency Parsing—0
Stacked Convolutional Deep Encoding Network for Video-Text Retrieval—0
Robust Stance Detection: Understanding Public Perceptions in Social Media—0
Standardizing Knowledge Engineering Practices with a Reference Architecture—0
Standing on the Shoulders of Giants: Reprogramming Visual-Language Model for General Deepfake Detection—0
Stanford University's Submissions to the WMT 2014 Translation Task—0
STAR: Synthesis of Tailored Architectures—0
State Fourier Diffusion Language Model (SFDLM): A Scalable, Novel Iterative Approach to Language Modeling—0
Stateful Large Language Model Serving with Pensieve—0
State-Regularized Recurrent Neural Networks—0
State Spaces Aren't Enough: Machine Translation Needs Attention—0
Statistical Analysis of Multilingual Text Corpus and Development of Language Models—0
Statistical Input Method based on a Phrase Class n-gram Model—0
Statistical investigations into the geometry and homology of random programs—0
Statistical Machine Translation Improvement based on Phrase Selection—0
Statistical Machine Translation with Automatic Identification of Translationese—0
Statistical Method of Building Dialect Language Models for ASR Systems—0
Statistical Rejection Sampling Improves Preference Optimization—0
Stay on topic with Classifier-Free Guidance—0
ST-BERT: Cross-modal Language Model Pre-training For End-to-end Spoken Language Understanding—0
Stealthy Jailbreak Attacks on Large Language Models via Benign Data Mirroring—0
Stealthy LLM-Driven Data Poisoning Attacks Against Embedding-Based Retrieval-Augmented Recommender Systems—0
Steering Language Model Refusal with Sparse Autoencoders—0
Steering Large Language Models with Feature Guided Activation Additions—0
Stereo-Talker: Audio-driven 3D Human Synthesis with Prior-Guided Mixture-of-Experts—0
Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets—0
STEVE Series: Step-by-Step Construction of Agent Systems in Minecraft—0
STLLM-DF: A Spatial-Temporal Large Language Model with Diffusion for Enhanced Multi-Mode Traffic System Forecasting—0
STOA-VLP: Spatial-Temporal Modeling of Object and Action for Video-Language Pre-training—0
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization—0
Stochastic Code Generation—0
Stochastic Contextual Bandits with Long Horizon Rewards—0
Stochastic Learning of Nonstationary Kernels for Natural Language Modeling—0
Stochastic Tokenization with a Language Model for Neural Text Classification—0
Stock Market Prediction with Deep Learning: A Character-based Neural Language Model for Event-based Trading—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