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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 6301–6350 of 17610 papers

TitleStatusHype
A Surprisingly Robust Trick for the Winograd Schema Challenge—0
A Survey : Neural Networks for AMR-to-Text—0
A Survey of Emerging Approaches and Advances in Video Generation—0
A Survey of Knowledge-Intensive NLP with Pre-Trained Language Models—0
A Survey of Confidence Estimation and Calibration in Large Language Models—0
A Survey of Large Language Model Agents for Question Answering—0
A Survey of Large Language Model-Based Generative AI for Text-to-SQL: Benchmarks, Applications, Use Cases, and Challenges—0
A Survey of Large Language Model-Powered Spatial Intelligence Across Scales: Advances in Embodied Agents, Smart Cities, and Earth Science—0
A Survey of Low-shot Vision-Language Model Adaptation via Representer Theorem—0
A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges—0
A Survey of Scaling in Large Language Model Reasoning—0
A Survey of the Evolution of Language Model-Based Dialogue Systems—0
A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends—0
A Survey on Large Language Model Hallucination via a Creativity Perspective—0
A Survey on Large Language Model-Based Social Agents in Game-Theoretic Scenarios—0
A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly—0
A Survey on LLM-based News Recommender Systems—0
A Survey on LLM-powered Agents for Recommender Systems—0
A Survey on Multimodal Large Language Models—0
A Survey on Neural Network Language Models—0
A Survey On Neural Word Embeddings—0
A Survey on Zero Pronoun Translation—0
Asymmetric Mutual Learning for Multi-source Unsupervised Sentiment Adaptation with Dynamic Feature Network—0
Asymptotics of Language Model Alignment—0
Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients—0
AsyncMLD: Asynchronous Multi-LLM Framework for Dialogue Recommendation System—0
A Syntactically Expressive Morphological Analyzer for Turkish—0
A Syntax Aware BERT for Identifying Well-Formed Queries in a Curriculum Framework—0
A Systematic Analysis of Hybrid Linear Attention—0
A Systematic Bayesian Treatment of the IBM Alignment Models—0
A Systematic Comparison of Phrase Table Pruning Techniques—0
A systematic review of geospatial location embedding approaches in large language models: A path to spatial AI systems—0
A Systematic Study of Performance Disparities in Multilingual Task-Oriented Dialogue Systems—0
A System Level Performance Evaluation for Superconducting Digital Systems—0
A Tale of Tails: Model Collapse as a Change of Scaling Laws—0
A Targeted Assessment of Incremental Processing in Neural Language Models and Humans—0
AgentOps: Enabling Observability of LLM Agents—0
A Taxonomy of Self-Handover—0
A text autoencoder from transformer for fast encoding language representation—0
A Text-Based Knowledge-Embedded Soft Sensing Modeling Approach for General Industrial Process Tasks Based on Large Language Model—0
A Text Classification Model Combining Adversarial Training with Pre-trained Language Model and neural networks: A Case Study on Telecom Fraud Incident Texts—0
ATFLRec: A Multimodal Recommender System with Audio-Text Fusion and Low-Rank Adaptation via Instruction-Tuned Large Language Model—0
ATHENA: Automated Tuning of Genomic Error Correction Algorithms using Language Models—0
A Theoretical Perspective for Speculative Decoding Algorithm—0
A Theory on Adam Instability in Large-Scale Machine Learning—0
A Tightly-coupled Unsupervised Clustering and Bilingual Alignment Model for Transliteration—0
A Time Series Multitask Framework Integrating a Large Language Model, Pre-Trained Time Series Model, and Knowledge Graph—0
A-TIP: Attribute-aware Text Infilling via Pre-trained Language Model—0
ATLANTIC: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science—0
ATLaS: Agent Tuning via Learning Critical Steps—0
Show:102550
← PrevPage 127 of 353Next →
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