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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 93519400 of 17610 papers

TitleStatusHype
Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start RecommendationsCode1
LyricWhiz: Robust Multilingual Zero-shot Lyrics Transcription by Whispering to ChatGPTCode1
A Hybrid System for Systematic Generalization in Simple Arithmetic ProblemsCode0
Benchmarking Large Language Model Capabilities for Conditional Generation0
CMATH: Can Your Language Model Pass Chinese Elementary School Math Test?0
RAPGen: An Approach for Fixing Code Inefficiencies in Zero-Shot0
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and BiasCode1
Palm: Predicting Actions through Language Models @ Ego4D Long-Term Action Anticipation Challenge 2023Code1
Pareto Optimal Learning for Estimating Large Language Model Errors0
An Adversarial Multi-Task Learning Method for Chinese Text Correction with Semantic Detection0
Chatlaw: A Multi-Agent Collaborative Legal Assistant with Knowledge Graph Enhanced Mixture-of-Experts Large Language ModelCode5
Enhancing Dialogue Generation via Dynamic Graph Knowledge AggregationCode1
Prompting Large Language Models for Zero-Shot Domain Adaptation in Speech Recognition0
S2SNet: A Pretrained Neural Network for Superconductivity DiscoveryCode0
Most Language Models can be Poets too: An AI Writing Assistant and Constrained Text Generation StudioCode2
Towards Language Models That Can See: Computer Vision Through the LENS of Natural LanguageCode2
Let Segment Anything Help Image Dehaze0
Protein-DNA binding sites prediction based on pre-trained protein language model and contrastive learningCode1
HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide ResolutionCode2
FLuRKA: Fast and accurate unified Low-Rank & Kernel Attention0
Paradigm Shift in Sustainability Disclosure Analysis: Empowering Stakeholders with CHATREPORT, a Language Model-Based Tool0
Extending Context Window of Large Language Models via Positional InterpolationCode6
CamemBERT-bio: Leveraging Continual Pre-training for Cost-Effective Models on French Biomedical Data0
Using Large Language Models to Provide Explanatory Feedback to Human Tutors0
MotionGPT: Human Motion as a Foreign LanguageCode3
Fine-Tuning Large Language Models for Answering Programming Questions with Code Snippets0
LM4HPC: Towards Effective Language Model Application in High-Performance Computing0
Self-Supervised Image Captioning with CLIP0
Kosmos-2: Grounding Multimodal Large Language Models to the WorldCode1
Ontology Enrichment from Texts: A Biomedical Dataset for Concept Discovery and PlacementCode0
Large Multimodal Models: Notes on CVPR 2023 Tutorial0
Transfer Learning across Several Centuries: Machine and Historian Integrated Method to Decipher Royal Secretary's Diary0
Fauno: The Italian Large Language Model that will leave you senza parole!Code1
Automatic Assessment of Divergent Thinking in Chinese Language with TransDis: A Transformer-Based Language Model Approach0
Composing Parameter-Efficient Modules with Arithmetic OperationsCode1
LongCoder: A Long-Range Pre-trained Language Model for Code Completion0
Low-Rank Prune-And-Factorize for Language Model Compression0
Language models are weak learners0
Interactive Design by Integrating a Large Pre-Trained Language Model and Building Information Modeling0
Revolutionizing Cyber Threat Detection with Large Language Models: A privacy-preserving BERT-based Lightweight Model for IoT/IIoT Devices0
The Neuro-Symbolic Inverse Planning Engine (NIPE): Modeling Probabilistic Social Inferences from Linguistic Inputs0
Spatio-temporal Storytelling? Leveraging Generative Models for Semantic Trajectory Analysis0
Thinking Like an Annotator: Generation of Dataset Labeling Instructions0
DesCo: Learning Object Recognition with Rich Language DescriptionsCode1
UAlberta at SemEval-2023 Task 1: Context Augmentation and Translation for Multilingual Visual Word Sense DisambiguationCode0
Multimodal Search on Iconclass using Vision-Language Pre-Trained Models0
Product Information Extraction using ChatGPTCode0
Implementing contextual biasing in GPU decoder for online ASRCode1
Exploring the Potential of AI-Generated Synthetic Datasets: A Case Study on Telematics Data with ChatGPT0
A Survey on Multimodal Large Language Models0
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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