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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 44014450 of 17610 papers

TitleStatusHype
CovidLLM: A Robust Large Language Model with Missing Value Adaptation and Multi-Objective Learning Strategy for Predicting Disease Severity and Clinical Outcomes in COVID-19 PatientsCode0
Boosting Zero-Shot Human-Object Interaction Detection with Vision-Language TransferCode0
CPE-Pro: A Structure-Sensitive Deep Learning Method for Protein Representation and Origin EvaluationCode0
Exposing the Limits of Video-Text Models through Contrast SetsCode0
TinyBERT: Distilling BERT for Natural Language UnderstandingCode0
A Hybrid Approach to Automatic Corpus Generation for Chinese Spelling CheckCode0
Crafting In-context Examples according to LMs' Parametric KnowledgeCode0
CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language ModelCode0
Bootstrapping Text Anonymization Models with Distant SupervisionCode0
CRCL at SemEval-2024 Task 2: Simple prompt optimizationsCode0
SUPP.AI: Finding Evidence for Supplement-Drug InteractionsCode0
An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language ModelsCode0
Self-Bootstrapped Visual-Language Model for Knowledge Selection and Question AnsweringCode0
Both Matter: Enhancing the Emotional Intelligence of Large Language Models without Compromising the General IntelligenceCode0
Creative GANs for generating poems, lyrics, and metaphorsCode0
An Embedded Deep Learning based Word PredictionCode0
Crisis Domain Adaptation Using Sequence-to-sequence TransformersCode0
CrisisSense-LLM: Instruction Fine-Tuned Large Language Model for Multi-label Social Media Text Classification in Disaster InformaticsCode0
Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model ReasoningCode0
An Empirical Analysis of Uncertainty in Large Language Model EvaluationsCode0
Extreme Classification in Log Memory using Count-Min Sketch: A Case Study of Amazon Search with 50M ProductsCode0
B-PROP: Bootstrapped Pre-training with Representative Words Prediction for Ad-hoc RetrievalCode0
BP-Transformer: Modelling Long-Range Context via Binary PartitioningCode0
F5C-finder: An Explainable and Ensemble Biological Language Model for Predicting 5-Formylcytidine Modifications on mRNACode0
FaaF: Facts as a Function for the evaluation of generated textCode0
FABLE: A Novel Data-Flow Analysis Benchmark on Procedural Text for Large Language Model EvaluationCode0
Critic-Driven Decoding for Mitigating Hallucinations in Data-to-text GenerationCode0
CroissantLLM: A Truly Bilingual French-English Language ModelCode0
A surprisal oracle for when every layer countsCode0
A Surprisingly Effective Fix for Deep Latent Variable Modeling of TextCode0
Brain-Like Language Processing via a Shallow Untrained Multihead Attention NetworkCode0
CrossBind: Collaborative Cross-Modal Identification of Protein Nucleic-Acid-Binding ResiduesCode0
An Empirical Comparison of Generative Approaches for Product Attribute-Value IdentificationCode0
Cross-Domain NER using Cross-Domain Language ModelingCode0
Fair and Argumentative Language Modeling for Computational ArgumentationCode0
1Cademy @ Causal News Corpus 2022: Enhance Causal Span Detection via Beam-Search-based Position SelectorCode0
Fair multilingual vandalism detection system for WikipediaCode0
Fairness-Aware Structured Pruning in TransformersCode0
Development and Validation of a Dynamic-Template-Constrained Large Language Model for Generating Fully-Structured Radiology ReportsCode0
Faithful and Plausible Natural Language Explanations for Image Classification: A Pipeline ApproachCode0
FakeClaim: A Multiple Platform-driven Dataset for Identification of Fake News on 2023 Israel-Hamas WarCode0
Cross-lingual Argument Mining in the Medical DomainCode0
Fake news detection using Deep LearningCode0
Cross-Lingual BERT Transformation for Zero-Shot Dependency ParsingCode0
Cross-lingual Contextualized Phrase RetrievalCode0
Falcon 2.0: An Entity and Relation Linking Tool over WikidataCode0
Adaptive User Modeling with Long and Short-Term Preferences for Personalized RecommendationCode0
Cross-lingual Information Retrieval with BERTCode0
An Empirical Evaluation of Word Embedding Models for Subjectivity Analysis TasksCode0
Fantastic Semantics and Where to Find Them: Investigating Which Layers of Generative LLMs Reflect Lexical SemanticsCode0
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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