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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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 47014750 of 17610 papers

TitleStatusHype
AudioFormer: Audio Transformer learns audio feature representations from discrete acoustic codesCode0
Can Textual Semantics Mitigate Sounding Object Segmentation Preference?Code0
Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining?Code0
Can We Guide a Multi-Hop Reasoning Language Model to Incrementally Learn at Each Single-Hop?Code0
Can We Learn Communication-Efficient Optimizers?Code0
Deep Natural Language Feature Learning for Interpretable PredictionCode0
Gender Biases and Where to Find Them: Exploring Gender Bias in Pre-Trained Transformer-based Language Models Using Movement PruningCode0
Deep learning incorporating biologically-inspired neural dynamicsCode0
Gender Encoding Patterns in Pretrained Language Model RepresentationsCode0
An Independent Evaluation of ChatGPT on Mathematical Word Problems (MWP)Code0
Can We Trust the Performance Evaluation of Uncertainty Estimation Methods in Text Summarization?Code0
Auditing Prompt Caching in Language Model APIsCode0
Deep Neural Representations for Multiword Expressions DetectionCode0
DeepRapper: Neural Rap Generation with Rhyme and Rhythm ModelingCode0
GeneMask: Fast Pretraining of Gene Sequences to Enable Few-Shot LearningCode0
A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic SegmentationCode0
Deep Residual Output Layers for Neural Language GenerationCode0
Chain of Visual Perception: Harnessing Multimodal Large Language Models for Zero-shot Camouflaged Object DetectionCode0
Generalizations across filler-gap dependencies in neural language modelsCode0
Generalizing and Hybridizing Count-based and Neural Language ModelsCode0
Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction TuningCode0
Deep-speare: A Joint Neural Model of Poetic Language, Meter and RhymeCode0
Generalizing Visual Question Answering from Synthetic to Human-Written Questions via a Chain of QA with a Large Language ModelCode0
General Point Model Pretraining with Autoencoding and AutoregressiveCode0
Adding A Filter Based on The Discriminator to Improve Unconditional Text GenerationCode0
Generate, Annotate, and Learn: NLP with Synthetic TextCode0
DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated TextCode0
Augmenting Biomedical Named Entity Recognition with General-domain ResourcesCode0
Deep Transformers with Latent DepthCode0
Generate then Refine: Data Augmentation for Zero-shot Intent DetectionCode0
DeepWalk: Online Learning of Social RepresentationsCode0
Defending against Insertion-based Textual Backdoor Attacks via AttributionCode0
Generating Data with Text-to-Speech and Large-Language Models for Conversational Speech RecognitionCode0
DagoBERT: Generating Derivational Morphology with a Pretrained Language ModelCode0
Generating Diverse and High-Quality Texts by Minimum Bayes Risk DecodingCode0
MCRanker: Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM RankersCode0
De-jargonizing Science for Journalists with GPT-4: A Pilot StudyCode0
Generating EDU Extracts for Plan-Guided Summary Re-RankingCode0
A Language Model for Spell Checking of Educational Texts in Kurdish (Sorani)Code0
Generating event descriptions under syntactic and semantic constraintsCode0
Careless Whisper: Speech-to-Text Hallucination HarmsCode0
Generating Hypothetical Events for Abductive InferenceCode0
An Invariant Learning Characterization of Controlled Text GenerationCode0
Augmenting Self-attention with Persistent MemoryCode0
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic lossCode0
Generating Medical Prescriptions with Conditional TransformerCode0
Generating Memorable Mnemonic Encodings of NumbersCode0
DeltaScore: Fine-Grained Story Evaluation with PerturbationsCode0
NegatER: Unsupervised Discovery of Negatives in Commonsense Knowledge BasesCode0
Generating Prototypes for Contradiction Detection Using Large Language Models and Linguistic RulesCode0
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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