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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

Showing 64516500 of 17610 papers

TitleStatusHype
KidneyTalk-open: No-code Deployment of a Private Large Language Model with Medical Documentation-Enhanced Knowledge Database for Kidney DiseaseCode0
Prompt Tuning or Fine-Tuning - Investigating Relational Knowledge in Pre-Trained Language ModelsCode0
Stacked AMR Parsing with Silver DataCode0
LAMOL: LAnguage MOdeling for Lifelong Language LearningCode0
Multi-system machine translation using online APIs for English-LatvianCode0
Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response TheoryCode0
Multi-FAct: Assessing Factuality of Multilingual LLMs using FActScoreCode0
Stance Reasoner: Zero-Shot Stance Detection on Social Media with Explicit ReasoningCode0
Linguistic Versus Latent Relations for Modeling Coherent Flow in ParagraphsCode0
UDALM: Unsupervised Domain Adaptation through Language ModelingCode0
Topic Classification of Case Law Using a Large Language Model and a New Taxonomy for UK Law: AI Insights into Summary JudgmentCode0
Semantic Coherence Markers for the Early Diagnosis of the Alzheimer DiseaseCode0
KL-Divergence Guided Temperature SamplingCode0
RALLRec+: Retrieval Augmented Large Language Model Recommendation with ReasoningCode0
MIP-GAF: A MLLM-annotated Benchmark for Most Important Person Localization and Group Context UnderstandingCode0
General Mechanism of Evolution Shared by Proteins and WordsCode0
Rethinking the Role of Proxy Rewards in Language Model AlignmentCode0
SemanticCAP: Chromatin Accessibility Prediction Enhanced by Features Learning from a Language ModelCode0
On the Effect of (Near) Duplicate Subwords in Language ModellingCode0
Stateful Memory-Augmented Transformers for Efficient Dialogue ModelingCode0
TopicRNN: A Recurrent Neural Network with Long-Range Semantic DependencyCode0
Semantic and sentiment analysis of selected Bhagavad Gita translations using BERT-based language frameworkCode0
Persona Knowledge-Aligned Prompt Tuning Method for Online DebateCode0
Personal Attribute Prediction from ConversationsCode0
Personal Information Leakage Detection in ConversationsCode0
Topics as Entity Clusters: Entity-based Topics from Large Language Models and Graph Neural NetworksCode0
Reference-less Analysis of Context Specificity in Translation with Personalised Language ModelsCode0
LINKED: Eliciting, Filtering and Integrating Knowledge in Large Language Model for Commonsense ReasoningCode0
PrOnto: Language Model Evaluations for 859 LanguagesCode0
Using Persuasive Writing Strategies to Explain and Detect Health MisinformationCode0
Misinformation Has High PerplexityCode0
Personalized Image Enhancement Featuring Masked Style ModelingCode0
Recurrent Hierarchical Topic-Guided RNN for Language GenerationCode0
Stealth edits to large language modelsCode0
LANGUAGE MODEL EMBEDDINGS IMPROVE SENTIMENT ANALYSIS IN RUSSIANCode0
Personalized Language Model for Query Auto-CompletionCode0
Looking for a Handsome Carpenter! Debiasing GPT-3 Job AdvertisementsCode0
Multi-task Pre-training Language Model for Semantic Network CompletionCode0
Semantically Meaningful Metrics for Norwegian ASR SystemsCode0
Semantically Grounded Object Matching for Robust Robotic Scene RearrangementCode0
Personalized Language Model Learning on Text Data Without User IdentifiersCode0
Understanding Language Modeling Paradigm Adaptations in Recommender Systems: Lessons Learned and Open ChallengesCode0
Personalized LLM for Generating Customized Responses to the Same Query from Different UsersCode0
Learning to Infer from Unlabeled Data: A Semi-supervised Learning Approach for Robust Natural Language InferenceCode0
Multi-Granularity Prediction for Scene Text RecognitionCode0
Stepwise Alignment for Constrained Language Model Policy OptimizationCode0
Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model TutorsCode0
StereoKG: Data-Driven Knowledge Graph Construction for Cultural Knowledge and StereotypesCode0
Topology-aware Preemptive Scheduling for Co-located LLM WorkloadsCode0
PropMEND: Hypernetworks for Knowledge Propagation in LLMsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Decay RNNValidation perplexity76.67Unverified
2GRUValidation perplexity53.78Unverified
3LSTMValidation perplexity52.73Unverified
4LSTMTest perplexity48.7Unverified
5Temporal CNNTest perplexity45.2Unverified
6TCNTest perplexity45.19Unverified
7GCNN-8Test perplexity44.9Unverified
8Neural cache model (size = 100)Test perplexity44.8Unverified
9Neural cache model (size = 2,000)Test perplexity40.8Unverified
10GPT-2 SmallTest perplexity37.5Unverified
#ModelMetricClaimedVerifiedStatus
1TCNTest perplexity108.47Unverified
2Seq-U-NetTest perplexity107.95Unverified
3GRU (Bai et al., 2018)Test perplexity92.48Unverified
4R-TransformerTest perplexity84.38Unverified
5Zaremba et al. (2014) - LSTM (medium)Test perplexity82.7Unverified
6Gal & Ghahramani (2016) - Variational LSTM (medium)Test perplexity79.7Unverified
7LSTM (Bai et al., 2018)Test perplexity78.93Unverified
8Zaremba et al. (2014) - LSTM (large)Test perplexity78.4Unverified
9Gal & Ghahramani (2016) - Variational LSTM (large)Test perplexity75.2Unverified
10Inan et al. (2016) - Variational RHNTest perplexity66Unverified
#ModelMetricClaimedVerifiedStatus
1LSTM (7 layers)Bit per Character (BPC)1.67Unverified
2HypernetworksBit per Character (BPC)1.34Unverified
3SHA-LSTM (4 layers, h=1024, no attention head)Bit per Character (BPC)1.33Unverified
4LN HM-LSTMBit per Character (BPC)1.32Unverified
5ByteNetBit per Character (BPC)1.31Unverified
6Recurrent Highway NetworksBit per Character (BPC)1.27Unverified
7Large FS-LSTM-4Bit per Character (BPC)1.25Unverified
8Large mLSTMBit per Character (BPC)1.24Unverified
9AWD-LSTM (3 layers)Bit per Character (BPC)1.23Unverified
10Cluster-Former (#C=512)Bit per Character (BPC)1.22Unverified
#ModelMetricClaimedVerifiedStatus
1Smaller Transformer 126M (pre-trained)Test perplexity33Unverified
2OPT 125MTest perplexity32.26Unverified
3Larger Transformer 771M (pre-trained)Test perplexity28.1Unverified
4OPT 1.3BTest perplexity19.55Unverified
5GPT-Neo 125MTest perplexity17.83Unverified
6OPT 2.7BTest perplexity17.81Unverified
7Smaller Transformer 126M (fine-tuned)Test perplexity12Unverified
8GPT-Neo 1.3BTest perplexity11.46Unverified
9Transformer 125MTest perplexity10.7Unverified
10GPT-Neo 2.7BTest perplexity10.44Unverified