SOTAVerified

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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 13101–13150 of 17610 papers

TitleStatusHype
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
StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction—0
STORE: Streamlining Semantic Tokenization and Generative Recommendation with A Single LLM—0
Stories in the Eye: Contextual Visual Interactions for Efficient Video to Language Translation—0
Storyboard guided Alignment for Fine-grained Video Action Recognition—0
Story Centaur: Large Language Model Few Shot Learning as a Creative Writing Tool—0
Story Cloze Task: UW NLP System—0
Strategic Data Ordering: Enhancing Large Language Model Performance through Curriculum Learning—0
Strategic Insights in Human and Large Language Model Tactics at Word Guessing Games—0
Stratified Prediction-Powered Inference for Hybrid Language Model Evaluation—0
StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant—0
Streaming Small-Footprint Keyword Spotting using Sequence-to-Sequence Models—0
StreamLink: Large-Language-Model Driven Distributed Data Engineering System—0
StreamVoice+: Evolving into End-to-end Streaming Zero-shot Voice Conversion—0
StreamVoice: Streamable Context-Aware Language Modeling for Real-time Zero-Shot Voice Conversion—0
StreetviewLLM: Extracting Geographic Information Using a Chain-of-Thought Multimodal Large Language Model—0
Strengthening Fake News Detection: Leveraging SVM and Sophisticated Text Vectorization Techniques. Defying BERT?—0
Strengthening Multimodal Large Language Model with Bootstrapped Preference Optimization—0
Strong Black-box Adversarial Attacks on Unsupervised Machine Learning Models—0
StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding—0
StrucTexTv3: An Efficient Vision-Language Model for Text-rich Image Perception, Comprehension, and Beyond—0
StructFormer: Document Structure-based Masked Attention and its Impact on Language Model Pre-Training—0
Structural Ambiguity and its Disambiguation in Language Model Based Parsers: the Case of Dutch Clause Relativization—0
Structural and Functional Decomposition for Personality Image Captioning in a Communication Game—0
Structural Embedding Projection for Contextual Large Language Model Inference—0
Structural Encoding and Pre-training Matter: Adapting BERT for Table-Based Fact Verification—0
Structural Language Models for Any-Code Generation—0
Structural Realization with GGNNs—0
Structural Reformation of Large Language Model Neuron Encapsulation for Divergent Information Aggregation—0
Structural Supervision Improves Learning of Non-Local Grammatical Dependencies—0
Structure-Accurate Medical Image Translation via Dynamic Frequency Balance and Knowledge Guidance—0
Structure-Aware Corpus Construction and User-Perception-Aligned Metrics for Large-Language-Model Code Completion—0
Structured Agent Distillation for Large Language Model—0
Structured Chain-of-Thought Prompting for Few-Shot Generation of Content-Grounded QA Conversations—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