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 They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.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

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Showing 13351–13400 of 17610 papers

TitleStatusHype
TACO: Pre-training of Deep Transformers with Attention Convolution using Disentangled Positional Representation—0
Prix-LM: Pretraining for Multilingual Knowledge Base Construction—0
StableMoE: Stable Routing Strategy for Mixture of Experts—0
Probing BERT’s priors with serial reproduction chains—0
Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data—0
Schema-Free Dependency Parsing via Sequence Generation—0
Towards Unified Prompt Tuning for Few-shot Learning—0
On the Use of Entity Embeddings from Pre-Trained Language Models for Knowledge Graph Completion—0
NSP-NER: A Prompt-based Learner for Few-shot NER Driven by Next Sentence Prediction—0
NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction—0
KinyaBERT: a Morphology-aware Kinyarwanda Language Model—0
On a Benefit of Masked Language Model Pretraining: Robustness to Simplicity Bias—0
Towards a Progression-Aware Autonomous Dialogue Agent—0
MATHion: Solving Math Word Problems with Logically Consistent Problems—0
Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings—0
Prompting as Multimodal Fusing—0
Plug-Tagger: A Pluggable Sequence Labeling Framework with Pre-trained Language Models—0
Your fairness may vary: Pretrained language model fairness in toxic text classification—0
What Works and Doesn't Work, A Deep Decoder for Neural Machine Translation—0
Unsupervised Dependency Graph Network—0
XLM-E: Cross-lingual Language Model Pre-training via ELECTRACode0
Using Structured Content Plans for Fine-grained Syntactic Control in Pretrained Language Model Generation—0
UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQL—0
UniPELT: A Unified Framework for Parameter-Efficient Language Model Tuning—0
Choose Your Programming Copilot: A Comparison of the Program Synthesis Performance of GitHub Copilot and Genetic Programming—0
AUTOMATED AUDIO CAPTIONING BY FINE-TUNING BART WITH AUDIOSET TAGSCode0
Calculating Question Similarity is Enough: A New Method for KBQA Tasks—0
Analysis of Data Augmentation Methods for Low-Resource Maltese ASR—0
Semantically Grounded Object Matching for Robust Robotic Scene RearrangementCode0
Joint Unsupervised and Supervised Training for Multilingual ASR—0
SocialBERT -- Transformers for Online SocialNetwork Language Modelling—0
Explainable Semantic Space by Grounding Language to Vision with Cross-Modal Contrastive Learning—0
HMD-AMP: Protein Language-Powered Hierarchical Multi-label Deep Forest for Annotating Antimicrobial Peptides—0
Self-Normalized Importance Sampling for Neural Language Modeling—0
SynthBio: A Case Study in Human-AI Collaborative Curation of Text Datasets—0
FPM: A Collection of Large-scale Foundation Pre-trained Language Models—0
Explaining Face Presentation Attack Detection Using Natural Language—0
Machine-in-the-Loop Rewriting for Creative Image CaptioningCode0
Effective Cross-Utterance Language Modeling for Conversational Speech Recognition—0
CoreLM: Coreference-aware Language Model Fine-Tuning—0
A text autoencoder from transformer for fast encoding language representation—0
Leveraging Advantages of Interactive and Non-Interactive Models for Vector-Based Cross-Lingual Information Retrieval—0
PhyloTransformer: A Discriminative Model for Mutation Prediction Based on a Multi-head Self-attention Mechanism—0
Integrating Pretrained Language Model for Dialogue Policy Learning—0
Detection of Hate Speech using BERT and Hate Speech Word Embedding with Deep Model—0
GTCOM Neural Machine Translation Systems for WMT21—0
Compressive Performers in Language Modelling—0
ArabicTransformer: Efficient Large Arabic Language Model with Funnel Transformer and ELECTRA ObjectiveCode0
HOTTER: Hierarchical Optimal Topic Transport with Explanatory Context RepresentationsCode0
A Fine-Grained Analysis of BERTScore—0
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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